Unit IV VISUAL REALISM & MODELING SOFTWARES VISUAL REALISM YEAR/COMPUTER AIDED... · 2017-09-30 · Unit – IV VISUAL REALISM & MODELING SOFTWARES VISUAL REALISM MET71 COMPUTER AIDED

Unit – IV

VISUAL REALISM & MODELING SOFTWARES

VISUAL REALISM

MET71 COMPUTER AIDED DESIGN

The most effective way to communicate new ideas and designs of engineers are visualization and hence, the visualization plays an important role in CAD/CAM. The performance of any CAD/CAM systems is evaluated on the basis of their ability of displaying realistic visual image. Visualization can be defined as a technique for creating images, diagrams or animations to communicate ideas. The visual realism concentrates basically on the visual appearance of objects. In this approach, various techniques of computer graphics are applied on the model to make it appear as realistic as possible. Projection and shading are two most common methods for visualizing geometric models. Orthographic projection is one of the oldest methods to represent new design ideas for complete dimensional referencing. But, it has the disadvantage of difficulty in interpreting various views and also time consuming. CAD uses isometric and perspective projections in addition to orthographic projections for generating rich visual images with complete design information. Visual realism can also convey appearance characteristics of the model such as colour and texture. By using such visual realism techniques, it is possible to make the user to feel that the images are real objects. It is also useful in determining the spatial relationship between objects as in the case of assembly modeling.

There are two important and popular form of visualization methods such as animation and simulation. The various kinematic mechanisms with number of links can be modeled and their motion can be simulated by using visual realism. Similarly, by using FEA technique, we can model and simulate the heat flow in a pipe, deformation in a beam or structure, electromagnetic field, etc. The heat flow can be simulated frame-by-frame for different time steps. In a similar way, it is also possible to verify the tool path of the numerical control (NC) by generating and displaying the motion of the tool path. It can be achieved by entering the numerical data of the path of the cutting tool as NC part programming. Also, the virtual realistic model may be used for marketing to access its acceptability before actually manufacture it.

Most of the cases, 3D models are used to create the visual real effect. An object may consist of number of vertices, edges, surfaces which are represented realistically in 3D modeling. The major problem in visualization of object is representing the depth of 3D object into 2D screens. Projecting 3D object into 2D screen displays the complex lines and curves which may not give a clear picture to interpret. The first step towards visual realism is to eliminate these ambiguities which can be obtained using hidden line removal (HLR), hidden surface removal (HSR) and hidden solid removal approaches.

There are further more approaches to achieve the visual realism such as shading, lighting, transparency and colouring. Surface and solid models can be shaded with two-step process. First, we need to remove the hidden surfaces and then shade only the visible portions. The highest level of visual realism can be achieved by shading. Lighting such as source and ambient lights flashed on the objects can be simulated. Lighting gives more clear and better shading representation for the object. Various colouring schemes can be modeled for different components of the assembly model based on the material of components. This approach is useful in identifying materials of the parts and it differentiates various assembled components. Transparency of the face enables the inner details to be viewed by reducing the intensity of the face. However, these approaches consume a lot of computing time and occupy plenty of memory space of the computer. But, now-a-days, computers with advanced and faster processors are available which makes these processes easier.

M.SRINIVASSAN, ASST. PROF 1 RGCET


Fig.4.1 Isometric view

Another basic method to achieve the visual realism is model clean-up. Model clean-up consists of three processes in sequence: (1) generating orthographic views of the model, (2) eliminating hidden lines in each view by applying visual realism principle and (3) changing the necessary hidden lines as dashed line and/or adding dimensions and text to the different views without redundant dimensions. A model clean-up can be done either manually or automatically using a suitable algorithm. Manual method provides a better control over the selection of lines to be removed. However, it is time-consuming, tedious and error-prone method. While implementing the automatic model clean-up, care should be taken to provide the control over various clean-up activities such as dimensioning, texting, hidden line removal etc. to the user so that they may feel more comfortable. Figure 4.2 and Figure 4.3 shows examples of a model before and after clean- up process.

Fig.4.2 A model before clean-up process



HIDDEN LINE REMOVAL

Fig.4.3 A model after clean-up process

As stated earlier, removing hidden line and surfaces greatly improve the visualization of objects by displaying clear and more realistic images. A typical example of an object before and after removal of hidden lines is shown in Figure 4.4. As it is shown, the appearance of the object is greatly complicated by the visibility of hidden details. Therefore, it is necessary to remove hidden details such as edges and surfaces. The edges and surfaces which need to be removed depending on its view port, viewing direction and viewing window. One of the most challenging problems considered in computer graphics is the determination of hidden edges and surfaces.

Fig.4.4 Hidden line removal

The hidden line elimination can be stated as, "For a given three dimensional scene, a given viewing point and a given direction eliminate from an appropriate two dimensional projection of the edges and faces which the observer cannot see".

Various hidden line and hidden surface removal algorithms have been developed over the years and a wide variety of algorithms exists today. The development of these algorithms is



based on the types of graphic display devices that they support and by the type of data structure, they operate on. These algorithms may be classified into object-space method and image- space method.

In object-space method, the object is described in the physical coordinate system. It compares the objects and parts of objects to each other within the scene definition to determine which surfaces are visible. This method performs the geometric calculation using floating point precision of the computer. Algorithms developed using this method are more accurate which is based on an image-space method. Object-space methods are generally used in hidden line removal algorithms. Image-space method is implemented in the screen coordinate system in which the objects are viewed. Hence, it performs the calculations with accuracy equal to the resolution. In an image-space algorithm, the visibility is decided point by point at each pixel position on the view plane. Hence, zooming of the object does not degrade its quality of display. Most of the hidden line and hidden surface algorithms use the image-space method. Hidden Line Elimination Process

The procedure for hidden line elimination process is shown in Figure 4.5. Three- dimensional data is a set of three-dimensional objects. Each object is defined by its geometry and topology. Example: Solid model of objects. The first step in the hidden line elimination process is that the 3D models have to be modified in such a way that it can identify faces and the order of their edges.

The next step is to apply a proper geometric transformation such as translation, rotation, reflection, mirroring to the 3D data to obtain the 2D image data. At this stage, the image contains all visible and invisible edges.

Then sorting operation is performed. Sorting is an operation which arranges a given set of records according to the selected criterion. The elements obtained in 2D image data are sorted using sorting techniques. These elements of a scene or its image have some interrelationship. The interrelationship between these basic elements is called coherence. The coherence determines the speed at which a 2D image can be changed. It can speed up the process under the dynamic conditions of model visualization.

The visibility technique normally checks for overlapping of pairs of polygons in the viewing plane. If the overlapping occurs, depth comparisons are used to determine if part or all of one polygon is hidden by another polygon.

Three dimensional object data

Two-dimensional (2D) image data

Sorting of 2D image data

Applications of visibility techniques

Elimination of hidden lines

Display the results

Fig.4.5 Hidden line Elimination process

The surface test to eliminate the back faces is usually sufficient to solve the hidden line if the image has no holes. Otherwise, a combination of techniques is required. In order to apply the visibility technique to the image data, the sorting of this data is required.



With the completions of sorting according to the visibility criteria set by the visibility techniques, the hidden edges have been identified and removed from the image data. The final step in this algorithm is to display the final images. Visibility Techniques

As discussed earlier, the visibility technique normally checks the overlapping of pairs of polygons in the viewing plane. There are different types of visibility techniques and algorithms exist to differentiate 2D elements. The simplest approach involves in evaluating the depth elements from the view point along the viewing direction. However, it leads to a situation where every single element needs to be compared with other elements on a view. Therefore, the following Visibility techniques are developed:

Minimax test Containment test Surface test Computing Silhouettes Edge intersection Segment comparisons Homogeneity test.

(a) Minintax test: This test compares whether two polygons overlap or not. Here, each polygon is enclosed in a

box by finding its maximum and minimum x and y coordinates. Therefore, it is termed as minimax test. Then these boxes are compared with each other to identify the intersection for any two boxes. If there is no intersection of two boxes as shown in Figure 4.6 (a), their surrounding polygons do not overlap and hence, no elements are removed. If two boxes intersect, the polygons may or may not overlap as shown in Figure 4.6 (b) & (C). If polygons do not overlap, hence, no elements are removed. If polygons overlap, a further technique of hidden line removal is applied. This test helps to reduce the number of comparison between all elements.

(b) Containment test:

Fig.4.6 Minimax test

This test checks whether the location of a given point is inside or outside of a given polygon. For a convex polygon, x and y coordinates value of the points is substituted into the line equation to see the results on the given edge. If the result of the sign is same, the points lie on the same side and vice versa.



For non-convex polygons, there are two methods used. The first method uses the sum of angle subtended by each edge of the polygon used to determine whether the location of a given point is inside or outside. If the sum of the subtended angle is 2π, the point is inside the polygon. If the subtended angle is zero, the point is outside the polygon. In the second method, a line is drawn from the point under testing it to infinity. If the lines are not intersecting with the polygon, the containment test for both extreme point of the edge generates similar results i.e. either both are inside or outside. If the line is intersected with the Polygon, the line will be segmented first and then the containment test is performed on each segment. Therefore, determining points on an element surrounded by other elements can help to decide whether the element is visible or not. (c) Back face /Surface test:

In a solid object, there are surfaces which are facing the viewer (front faces) and there are surfaces which are opposite to the viewer (back faces). These back faces contribute to approximately half of the total number of surfaces. A back face test is used to determine the location of a surface with respect to other surface. Therefore, this test can provide an efficient way of implementing the depth comparison to remove the faces which are not visible in a specific view port. As we know, every surface has a surface normal. According to this test principle, the viewing direction needs to be correlated with its surface normal. Faces whose surface normal has a positive component in z direction are visible and those whose surface normal has a negative z component are not visible.

(d) Computing silhouettes:

Fig.4.7 Surface test

Silhouettes are a set of edges which separate a visible faces from invisible faces of an object with respect to the viewing direction as shown in Figure 4.8. An edge is the intersection of one visible face and one invisible face is termed as silhouettes. The intersection of two invisible faces generates an invisible edge where as an edge produced by the intersection of two visible faces is visible. Silhouettes are computed by using the sign of component of surface normal along the viewing direction.



Fig.4.8 Silhouettes

HIDDEN LINE REMOVAL ALGORITHMS

The visibility techniques discussed so far can identify the visibility in a 2D image space for the displayed image. Algorithms are used to finalize these hidden lines and surfaces and it is to remove them in a specific view. The wide varieties of hidden line elimination algorithms exist. These algorithms are based on one of the following three approaches.

i. Edge-oriented approach ii. Silhouette (contour) originated approach or iii. Area-Oriented approach.

The various algorithms that utilize one or more of visibility techniques discussed earlier d follow one of the above three approaches are as follows.

i. Depth algorithm or z algorithm or Priority algorithm ii. Area-oriented algorithms. iii. Overlay algorithm iv. Robert's algorithm v. Depth-buffer algorithm or z-buffer algorithm

vi. Area-coherence algorithm or Warnock's algorithm vii. Ray tracing algorithm

Depth or Priority Algorithm

This algorithm is based on sorting of all faces of polygon in the scene according to its depth in viewing direction. It can be done by the following steps.

All surfaces of polygons are sorted (ordered) according to the smallest z- coordinate on each surface.

The surface with the largest depth (z-value) is compared with all other surfaces in the list to compare if there is any overlap in the z-coordinate.

Any ambiguities can be resolved by splitting the polygons when z-coordinate of polygons overlap (refer Figure 4.9).

Figure 4.9 Depth-sort Algorithm overlapping of polygons in the depth direction

If there is no overlap, then its scan is converted to fill the frame buffer.



The same procedure is followed for all other surfaces in the list till and there is no overlap. Scan converts each polygon in ascending order from back to front in terms of z-

coordinate. When any face intersects more than one face, other visibility tests are required to resolve

ambiguities. No priority is assigned if no face / edge intersect. The priority is higher for a face coming first in viewing direction. So, this algorithm is called priority algorithm. This algorithm is also called painter's algorithm because it utilizes the procedure followed by painting artists during oil painting. An oil painter paints the background colours first and then it adds the distant objects. Then he adds the nearer objects in the order of decreasing depth. At the end, the foreground objects are drawn to the canvas over the background and others are already drawn objects. Each layer of paint covers up the previous layer. Using a similar technique, we first sort surfaces according to their distance from the view plane.

Fig.4.10 Painter’s algorithm

In this algorithm, the following tests are made for each surface that overlaps with the other surface P. The tests are listed in the order of increasing difficulty. If any one of these tests is true, no reordering is necessary for that surface and it is scan converted. For example two surfaces that overlap in the xy plane but have no depth overlap are shown in Figure 4.10 Since, there is no depth overlaps occurring in this case, the surface P is scan-converted.

Assume that surface P is currently at the head of the sorted list before scan converting it to

the frame buffer and it is tested against each surface Q whose z-extent overlaps that is P. The following tests of increasing complexity are then carried out.

(1) The bounding rectangles in the xy plane for the two surfaces do not overlap.

(2) Surface P is completely behind the overlapping surface relative to the viewing position. (3) The overlapping surface is completely in front of P relative to the viewing position. (4) The projections of the two surfaces onto the view plane do not overlap.



Fig.4.11 Two surfaces with depth overlap but no overlap in z direction

Fig.4.12 Two surfaces with depth overlap but no overlap in x direction

Among these tests, test 1 is performed in two parts. The surfaces are checked for overlap in the x direction first and then these are checked for overlap in the y direction. If the surfaces of P and Q do not overlap, then the surfaces do not overlap, hence, their ordering is immaterial. For example, surfaces that overlap in the z direction but not in the x direction are shown in Figure 4.11 and Figure 4.12.

HIDDEN SURFACE REMOVAL

The hidden surface removal is the procedure used to find which surfaces are not visible from a certain view. A hidden surface removal algorithm is a solution to the visibility issue, which was one of the first key issues in the field of three dimensional graphics. The procedure of hidden surface identification is called as hiding, and such an algorithm is called a 'hider'. Hidden surface identification is essential to render a 3D image properly, so that one cannot see through walls in virtual reality.

Hidden surface identification is a method by which surfaces which should not be visible to the user are prohibited from being rendered. In spite of benefits in hardware potential there is still a requirement for difficult rendering algorithms. The accountability of a rendering engine is to permit for bigger world spaces and as the world's size approaches infinity the rendering engine should not slow down but maintain at constant speed.

There are many methods for hidden surface identification. They are basically a work out in sorting, and generally vary in the order in which the sort is executed and how the problem is subdivided. Sorting more values of graphics primitives is generally done by divide. Z - buffer algorithm

In Z-buffering, the depth of 'Z' value is verified against available depth value. If the present pixel is behind the pixel in the Z-buffer, the pixel is eliminated, or else it is shaded and its depth value


MET71 COMPUTER AIDED DESIGN changes the one in the Z-buffer. Z-buffering helps dynamic visuals easily, and is presently introduced effectively in graphics hardware.

Depth buffering is one of the easiest hidden surface algorithms

It keeps follow of the space to nearest object at every pixel position.

Initialized to most negative z value.

when image being drawn, if its z coordinate at a position is higher than z buffer value, it is drawn, and new z coordinate value is stored; or else, it is not drawn

If a line in three dimensional is being drawn, then the middle z values are interpolated:

linear interpolation for polygons, and can calculate z for more difficult surfaces. Basic operations:

1. compute y range of an obj ect 2. compute x range of a given scan line of an object 3. Calculate intersection point of a object with ray through pixel position (x,y).

Warnock algorithm

The Warnock algorithm is a hidden surface algorithm developed by John Warnock that is classically used in the area of graphics. It explains the issues of rendering a difficult image by recursive subdivision of a view until regions are attained that is trivial to evaluate. Similarly, if the view is simple to compute effectively then it is rendered; else it is split into tiny parts which are likewise evaluated for simplicity. This is a algorithm with run-time of O(np), where p is the number of pixels in the viewport and n is the number of polygons.

The inputs for Warnock algorithm are detail of polygons and a viewport. The good case is that if the detail of polygons is very simple then creates the polygons in the viewport. The continuous step is to divide the viewport into four equally sized quadrants and to recursively

identify the algorithm for each quadrant, with a polygon list changed such that it contains polygons that are detectable in that quadrant.

1. Initialize the region. 2. Generate list of polygons by sorting them with their z values. 3. Remove polygons which are outside the area. 4. Identify relationship of each polygon. 5. Execute visibility decision analysis:

a) Fill area with background color if all polygons are disjoint,



b) Fill entire area with background color and fill part of polygon contained in area with color of polygon if there is only one contained polygon, c) If there is a single surrounding polygon but not contained then fill area with color of surrounding polygon.

d) Set pixel to the color of polygon which is closer to view if region of the pixel (x,y) and if neither of (a) to (d) applies calculate z- coordinate at pixel (x,y) of polygons.

6. If none of above is correct then subdivide the area and Go to Step 2. HIDDEN SOLID REMOVAL

The hidden solid removal issue involves the view of solid models with hidden line or surface eliminated. Available hidden line algorithm and hidden surface algorithms are useable to hidden solid elimination of B-rep models. The following techniques to display CSG models:

1. Transfer the CSG model into a boundary model. 2. Use a spatial subdivision strategy. 3. Based on ray sorting.

Ray-Tracing algorithm

A ray tracing is a method for creating an image by tracing the path of light via pixels in an image

plane and reproducing the effects of its meets with virtual objects. The procedure is capable of

creating a high degree of visual realism, generally higher than that of usual scan line techniques,

but at a better computational. This creates ray tracing excellent suited for uses where the image

can be rendered gradually ahead of time, similar to still images and film and TV visual effects,

and more badly suited for real time environment like video games where speed is very important.

Ray tracing is simulating a wide range of optical effects, such as scattering, reflection and

refraction.





For every pixel in image

{

Generate ray from eye point passing via this pixel

Initialize Nearest ‘T’ to ‘INFINITY’

Initialize Nearest Object to NULL For each object in scene

{

If ray intersects this image

{

If t of intersection is less than Nearest T

{

Set Nearest T to t of the intersection

Set Nearest image to this object

}

}

}

If Nearest image is NULL

{

Paint this pixel with background color

}

Else

{

Shoot a ray to every light source to check if in shadow

If surface is reflective, generate reflection ray

If transparent, generate refraction ray

Apply Nearest Object and Nearest T to execute shading function

Paint this pixel with color result of shading function

}

}

Optical ray tracing explains a technique for creating visual images constructed in three

dimensional graphics environments, with higher photorealism than either ray casting rendering



practices. It executes by tracing a path from an imaginary eye via every pixel in a virtual display,

and computing the color of the object visible via it.

Displays in ray tracing are explained mathematically by a programmer. Displays may also

incorporate data from 3D models and images captured like a digital photography.

In general, every ray must be tested for intersection with a few subsets of all the objects in the

view. Once the nearest object has been selected, the algorithm will calculate the receiving light at

the point of intersection, study the material properties of the object, and join this information to

compute the finishing color of the pixel. One of the major limitations of algorithm, the reflective or

translucent materials may need additional rays to be re-cast into the scene.

Advantages of Ray tracing:

1. A realistic simulation of lighting over other rendering.

2. An effect such as reflections and shadows is easy and effective.

3. Simple to implement yet yielding impressive visual results.

Limitation of ray tracing:

Scan line algorithms use data consistency to divide computations between pixels, while

ray tracing normally begins the process a new, treating every eye ray separately.

SHADING

Shading defines to describe depth perception in three dimensioning models by different levels of

darkness. Shading is applied in drawing for describes levels of darkness on paper by adding

media heavy densely shade for darker regions, and less densely for lighter regions.

There are different techniques of shading with cross hatching where perpendicular lines of

changing closeness are drawn in a grid pattern to shade an object. The closer the lines are

combining, the darker the area appears. Similarly, the farther apart the lines are, the lighter the

area shows.

Shading



Image with edge lines

The image shown in figure 3.8 has the faces of the box rendered, but all in the similar color. Edge lines have been rendered here as well which creates the image easier to view.

The image shown in figure 3.9 is the same model rendered without edge lines. It is

complicated to advise where one face of the box ends and the next starts.

The image shown in figure 3.10 has shading enabled which makes the image extra

realistic and makes it easier to view which face is which.

Shading techniques:

In computer graphics, shading submits to the procedure of changing the color of an object

in the

3D view, a photorealistic effect to be based on its angle to lights and its distance from

lights. Shading is performed through the rendering procedure by a program called a ‘Shader’. Flat

shading and Smooth shading are the two major techniques using in Computer graphics.

COLOURING

Colouring is useful for creating geometry and displaying images. It is also possible to

differentiate the different geometry by assigning different colours to each of them. The use of

colour may be extended to finite element analysis in which it is used to display the different heat

intensities or stress intensities in the model.

There are two types of colours: chromatic colour and achromatic colour. Chromatic

colours are provided multi-colour image in the display whereas achromatic colours provide only

black-and-white displays. Achromatic colour can have the variation of three different patterns

such as white, black, and various levels of gray which is a combination of white and black. These

variations are achieved by assigning the different intensity values. The intensity value of 1

provides white colour whereas 0 displays the black colour. More pleasing effects to the human

vision system can be produced by chromatic colours. But they are very complex subject which

deals both physics and physiology. However, fundamental concepts are discussed here.



The human vision system interprets electromagnetic energy with wavelengths between

400 and 700 nanometers as visible light. The various colours produced by different wavelengths

are given in Table 3.1.

S. No.

Colour Wave-Length

Nanometer

1. Violet 400

2. Blue 450

3. Cyan 500

4. Green 550

5. Yellow 600

6. Orange 650

7. Red 700

A method for explaining the properties or behavior of colour within some particular context

is called colour models. Single colour model cannot describe all aspects of colour, so different

colour models are used in computer graphics to help in describing the different perceived

characteristics of colour.

Colour Models

A colour model is an orderly system for creating a whole range of colours from a small set

of primary colours. There are two types of colour models: subtractive and additive. Additive colour

models use light to display colour while subtractive models use printing inks. Examples of

additive light are the electro-luminance produced by CRT or TV monitors, LCD projectors.

Colours perceived in additive models are the result of transmitted light. Colours perceived in

subtractive models are the result of reflected light. There are number of colour models available.

Some of the important colour models are as follows:

(i) RGB model

(ii) CMY model

(iii) YIQ model

(iv) HSV model

(v) HSL model.

i. RGB model

The RGB model is additive. In the RGB model, the convergence of the three primary additive

colours such as red (R), green (G) and blue (B) produces white. For a light, the numbers

correspond to a percentage of full intensity for each colour. If R, G, and B values are I then it will

produce white colour. If R » G = B = 0, the colour is black. If the values are 0.5, the colour is still

white but only at half intensity, so it appears gray. If R = G = 1 and B = 0 (full red and green with

no blue), the light appears yellow. Figure 3.33 shows the RGB colour model which is described in

Cartesian coordinates. The main diagonal of the cube is the locus of equal amount of each

primary colour. Hence, it represents the gray scale value.



RGB model is more suitable for quantifying direct light such as the one generated in a CRT

monitor, TV screens.

ii. CMY model:

The CMY model is subtractive. In the CMY model, the convergence of the three primary

colours such as cyan (C), magenta (M) and yellow (Y) produces white as shown in Figure 3.34. In

contrast to colour on the monitor, the colour in printing acts subtractive and not additive. A printed

colour which looks red absorbs the other two components G and B and it reflects R. Thus, its

(internal) colour is G + B = Cyan. Similarly, R + B = Magenta and R + G = Yellow. Thus, the CMY

coordinates are just the complements of the RGB. In the CMY model, point (1, 1, 1) represents

black because all components of the incident light are subtracted. The origin represents the white

light. Equal amounts of each of the primary colours produce grays along the main diagonal of the

cube. A combination of cyan and magenta ink produces blue because the red and green

components of the incident light are absorbed. Other colour combinations are obtained by a

similar subtractive process.

The conversion from an RGB representation to a CMY representation with the matrix

transformation can be expressed by


1 = 1 −

1


Where the white is represented in the RGB system as the unit column vector. Similarly, we

convert from a CMY colour representation to an RGB representation with the matrix

transformation.

1 = 1 −

1

Where black is represented in the CMY system as the unit column vector.

iii. YIQ model:

The YIQ model is used for raster colour graphics. In this colour model, the parameter Y is

same as in XYZ model. Brightness information is contained in Y parameter while chromaticity

information (hue and saturation) is incorporated into I and Q parameters. Combinations of red,

green and blue intensities are chosen for the Y parameter to yield the standard luminosity curve.

Since Y contains the luminance information, black and white television monitors use only Y

signal. Parameter I contains orange-cyan hue information which provides the flesh-tone shading

and the parameter Q carries green-magenta hue information.

The conversion from RGB values to YIQ values is accomplished with the following

transformation.

0.299 0.587 0.144 = 0.596 −0.275 −0.321 −

0.212 −0.528 0.311

Similarly, we convert from a YIQ colour representation to an RGB representation the matrix

transformation.

iv. HSV model:

0.299 0.587 0.144 = 0.596 −0.275 −0.321 −

0.212 −0.528 0.311

Both RGB and CMY colour models described earlier are hardware oriented models whereas

the HSV model is user oriented. It uses the colour descriptions which have more intuitive appeal

to a user. The colour specification in this model can be given by selecting a spectral colour and

the amounts of white and black. Colour parameters in this model are hue (H), saturation (S) and

value (V). The boundary of the hexagon represents the various hues and it is used as the top of

the HSV hexcone (i.e. six-sided pyramid) as shown in Figure 3.33. The top of the hexcone is

derived from the RGB cube.



Hue H is represented as an angle about the vertical axis ranging from 0° at red through 360°.

Vertices of the hexagon are separated by 60° intervals. Yellow is at 60°, green at 120°, and cyan

opposite red at H = 180°. Complementary colours are 180° apart.

Saturation S varies from 0 to 1. It is represented in this model as the ratio of the purity of a

selected hue to its maximum purity at S = 1. A selected hue is said to be half pure at the value

S=0.5. At S = 0, the gray scale is produced.

The value V varies from 0 at the apex of the hexcone to 1 at the top. The apex represents

black. At the top of the hexcone, colours have their maximum intensity. When V=1 and S=1, we

have the "pure" hues. White is the point at V = 1 and S = 0.

v. HSL model:

This model is also based on intuitive colour parameters. Colour parameters in this model

are hue (H), saturation (S) and lightness (L). This model has the double-cone representation as

shown in Figure 3.36.



The hue specifies the angle around the vertical axis of the double hexcone. In this model,

H=0° corresponds to blue. The remaining colours are specified around the perimeter of the cone

in the same order as in the HSV model. Magenta is at 60°, red is at 120° and cyan is located at

180°. Again, the complementary colours are 180° apart on the double cone.

Saturation parameter S specifies the relative purity of a colour. This parameter varies from

0 to 1, and pure hues are produced for S = 1 and L = 0.5. As S decreases, the hues are become

less pure. At S = 0, the gray scale is produced.

The lightness L is represented in the vertical axis. If L = 0, black colour is produced and

white is produced at L = 1. Gray scale is along L axis and the "pure hues" lie on the L = 0.5 plane.

COMPUTER ANIMATION

Animation is the process of illusion of continuous movement of objects created by a series

of still images with elements that appear to have motion. Each still image is called a frame.

Animation may also be defined as the process of dynamically creating a series of frames of a set

of objects in which each frame is an alteration of the previous frame. In order to animate

something, the animator has to be able to specify directly or indirectly how the 'thing' has to move

through time and space. Animation can be achieved by the following ways.

(a) By changing the position of various elements in the scene at different time frames in a

particular sequence



(b) By transforming an object to other object at different time frames in a particular

sequence

(c) By changing the colour of the object at different time frames in a particular sequence

(d) By changing the light intensities of the scene at different time frames in & particular

sequence.

Among these different methods, the most effective way is the first one.

The animation can be achieved either conventionally or traditionally using manual work or

using computer multimedia for producing movies, cartoons, logos and advertisements. In

conventional or traditional method, most of the animation was done by hand. All frames in 8

animation had to be drawn by hand. Since each second of animation requires 24 frames (film),

the amount of work required to create even the shortest of movies can be tremendous, however,

there are no calculations or physical principles required in this method. The motion should look

like real one which is the only criteria to create this type of animation. Animations created during

early days to create cartoon characters are the example of this type of animation.

The computer animations are mostly used now-a-day as the computer techniques evolved

over the years. This technique produces more realistic images and motions as real one. In this

type of animation, physical laws using variety of calculations arc utilized. Hence, the animation

creation is considered as a science rather than art. There are number of animation software

available in the market for producing human body motion based on Kinematic or dynamic

analysis. Typical applications of computer animation are entertainment (motion pictures and

cartoons), advertising, scientific and engineering studies, and training and education. Animation

is also useful for modeling and simulation of engineering problems where large amount of

calculations and scientific data are involved. For example, in finite element analysis we may need

to create series of images with different colouring plots at different time intervals to display the

result in sequence. It can be achieved by computer animation techniques. There are number of

entertainment animations used in movies, advertisements and computer games.

These animations use modeling of muscles and human body kinematics to create facial

expressions, deformable body shape, unrealistic fight sequence, transformations etc.

Applications of Animation

There are several areas where the animation can be extensively used. These areas can be

arbitrarily divided into five categories.

1. Television:

TV has used it for titles, logos and inserts as a powerful motivator for the rapid development

of animation. But its main uses are in cartoons for children and commercials for a general

audience.

2. Cinema:

Animation as a cinematic technique has always held an important role in this industry.

Complete animation films are still produced by the cinema industry. But, it is also a good way of

making special effects and it is frequently used for titles and generics.


3. Government:


Animation is an excellent method of mass communication and governments are of course,

great consumer of such techniques for the publicity.

4. Education and research:

Animation can be extensively used for educational purposes. Fundamentals concepts are

easily explained to students using visual effects involving motion. Finally, animation can be a

great help to research teams because it can simulate the situations, e.g., in medicine or science.

5. Business:

The role of animation in business is very similar to its role in government. Animation is useful

for marketing, personnel education and public relations.

6. Engineering:

Engineers do not require the realistic images the entertainment field demands. It must be

possible to identity unambiguously each separate part and the animation must be produced

quickly.

PARAMETRIC AND VARIATIONAL MODELING

The term parametric modeling denotes the use of parameters to control the dimensions

and shape of CAD models. Think of a rubber CAD model that can be stretched and deformed

through various controls, but cannot be ripped or torn. The manipulation of a CAD model of a

single part could be through overall part dimensions or through the dimensions of features.

Things get considerably more interesting if a parameterized assembly model is constructed.

Changes in assembly dimensions or in part dimensions can cause changes in assembly and part

shapes or in parts' assembled positions. Generally, it can be very useful to explore design spaces

by manipulating parametric CAD models - creating multiple instantiations of a design and

analyzing their properties.

There are two broad approaches parametric modeling:

parametric geometry

variational geometry

In general, the term parametric geometry refers to a 1-way evaluation of parametric relationships,

much like a spreadsheet. On the other hand, the relationships in variational geometry models can

be bi-directional.

Variational geometry solvers are typically nonlinear, simultaneous equation solvers. The

underlying mathematics suggests that variational geometry is more general and powerful, but in

practice it is the command set in CAD systems that really controls modeling generality and power

Parametric modeling solves constraints by replacing symbolic variables by values that are

computed sequentially from previously computed variables.

Variational modeling uses equations to represent constraints and solve them

simultaneously. The difference is captured by the difference between defining a variable via a

formula or implicitly.

FEATURE BASED MODELING



Feature-based modeling approach is more desirable in constructing solid models, in which

designers use features that correspond to physical entities to construct solid models, instead of

dealing with primitive geometric entities, such as points, curves, and solid primitives. The features

available in CAD are usually designed to relate to how engineers think in their design and

manufacturing work. The parametric modeling method allows designers to create solid models in

such a way that by varying a few parameters (e.g., geometric dimensions), the solid models

rebuild automatically as intended (i.e., capturing design intent). For example, a hole in the block

shown in Figure 3.12a is intended to stay at the middle of the block when the width of the block

changes. To capture this design intent, first the sketch profile of the base block must be fully

defined (Figure 3.12b), with dimension d2 as a design variable that is to vary. The hole must be

placed to the profile of the base block with its width dimension (d1 in Figure 3.12c) related to that

of block width d2, as dl = 0.5d2. This one-way parameter assignment is essentially parametric

modeling.

In most CAD, the base block is a protrusion feature generated by extruding the sketch profile

shown in Figure 3.12b along an extrusion direction that is normal to the sketch profile. The hole is

an extrude cut feature that does not require users to sketch its profile, which is called a pick-and-

place feature.

FIGURE 3.12 (a) The Block Example for the Illustration of Design Intent Capturing Using

Feature-based Parametric Solid Modeling Method, (b) Sketch Profile of the Base Block with

Width Dimension d2 Shown, (c) Position of the Hole by Dimension d1, which can be

Parametrically Related to Dimension d2.

S.No

.

Parametric & Feature based CAD

Systems

Conventional CAD Systems

1. Solid Model Wireframe and Solid Model

2. Parametric Model Fixed-dimension Model

3. Feature-based Modeling Primitive-based Modeling

4. A Single Data Structure and Full

Associativity

Function-Oriented Data Structures with

Format Interpreters

5. Subject-oriented Sub-modeling Systems A Single Geometry-Based System



6. Manufacturing Information Associated with

Features

Texts Attached to Geometry Entities

7. Generation of an Assembly by Assembling

Components

Generation of an Assembly by Positioning

Components

BEHAVIOR MODELING

Behavior modeling is the latest development in mechanical CAD. It gives the designers

more efficient and adaptable ways of creating designs. It helps to synthesize required functional

behavior, design context and geometry. Through an intelligent process of knowledge capture and

iterative solving behavior modeling allows engineers to pursue highly innovative and robust

designs. The process of behavior modeling involves: Smart models: These encapsulate

engineering intelligence. Designs are created using feature based techniques, which capture

geometry, specifications, design intent, and process knowledge-all at the design level.

Engineering objective based design: Design tools use feature based design specifications within

the smart model to drive and adapt product design. Using objective driven functions, engineers

can arrive at an optimum design, even in designs with several variables and constraints and

multiple objective criteria. Open extensible environment: This facilitates associative bi-directional

communication to any external application like analysis, manufacturing etc. at the feature level of

the design ensuring that model reflects the changes incorporated in other applications.

Behavior modeling helps to create designs which are more innovative, differentiable and

more responsive to customers’ requirements. With the help of objective driven design process

engineers can focus on key design issues, and evolve optimal design solutions for better

performance and functionality.

Behavior modeling helps to make electronic product designs more complete.

Behavior modeling strategy advances feature-based modeling to accommodate a set of

adaptive process features that go beyond the traditional core geometric features. These features

accommodate a variety of information that further specifies the intent and performance of the

design. There are two distinct categories of adaptive design. Application features describe

process information. Behavioral features contain engineering and functional specifications.

Application features encapsulate product and process information.

Behavioral features define component assembly connectivity, using welds, or pins or

slider joints. When behavioral features consist of assembly connectivity information, including any

assembly constraints, the assembly design process automatically implements that information to

execute functional behavior and purpose. By capturing original design intent, product designs

retain their integrity, robustness, and performance while adapting to market and engineering

changes. The adaptive process features make smart models highly flexible. As the engineers

make changes to the smart models, the models regenerate to accommodate all their features and

context. This highly flexible adaptation makes smart models to respond to changes in their

environment. Objective driven design automatically optimizes designs to meet any number of



objectives captured in the smart model by adaptive process features. It can automatically resolve

conflicting objectives. In smart models the specifications can be used to drive the design process.

An overview of modeling software like PRO-E, CATIA, IDEAS, SOLID EDGE and other advanced

Softwares.

OVERVIEW OF MODELING SOFTWARES:

In 3D computer graphics, 3D modeling (or modelling) is the process of developing a mathematical representation of any three-dimensional surface of an object (either inanimate or living) via specialized software. The product is called a 3D model. It can be displayed as a two- dimensional image through a process called 3D rendering or used in a computer simulation of physical phenomena. The model can also be physically created using 3D printing devices.

Models may be created automatically or manually. The manual modeling process of preparing geometric data for 3D computer graphics is similar to plastic arts such as sculpting. 3D modeling software is a class of 3D computer graphics software used to produce 3D models. Individual programs of this class are called modeling applications or modelers. List of 3D modeling software

1. PRO-E, 2. CATIA, 3. IDEAS, 4. SOLID EDGE 5. Autodesk Inventor etc.

PRO-E

Pro/ENGINEER is a computer graphics system for modeling various mechanical designs and for performing related design and manufacturing operations. The system uses a 3D solid modeling system as the core, and applies the feature-based, parametric modeling method. In short, Pro/ENGINEER is a feature-based, parametric solid modeling system with many extended design and manufacturing applications.

Pro/ENGINEER is the first commercial CAD system entirely based upon the feature- based design and parametric modeling philosophy. Today many software producers have recognized the advantage of this approach and started to shift their product onto this platform. Pro/ENGINEER Functionality The basic functionality of Pro/ENGINEER is broken into several areas:

Part Design Assembly Design Design Documentation (Drawings) General Functionality

An Overview (by Parametric Technology Corp.) Ease of Use:

Pro/ENGINEER was designed to begin where the design engineer begins with features and design criteria. Pro/ENGINEER's cascading menus flow in an intuitive manner, providing logical choices and pre-selecting most common options, in addition to short menu descriptions and full on-line help. This makes it simple to learn and utilize even for the most casual user. Expert users employ Pro/ENGINEER's "map keys" to combine frequently used commands along with customized menus to exponentially increase their speed in use. Because Pro/ENGINEER provides the ability to sketch directly on the solid model, feature placement is simple and accurate. Full Associativity: Pro/ENGINEER is based on a single data structure, with the ability to make change built into the system. Therefore, when a change is made anywhere in the development process, it is propagated throughout the entire design-through-manufacturing process, ensuring consistency in all engineering deliverables.

Parametric, Feature-Based Modeling: Pro/ENGINEER's features are process plans with imbedded intelligence and are easy to use, while at the same time, powerful enough to fillet, round, and shell even the most complex geometry. These features contain non-geometric information, such as manufacturing processes and associated costs, as well as information about location and relationships. This means that features do not require coordinate systems for


MET71 COMPUTER AIDED DESIGN placement, and they "know" how they are related to the rest of the model. As a result, changes are made quickly and always adhere to the original design intent. Powerful Assembly Capabilities: Assembling components is easy with Pro/ENGINEER simply tell the system to "mate," "insert," or "align" the components and they are assembled, always maintaining the design intent. Also, the components "know" how they are related, so if one changes, either positionally or geometrically, the other will change accordingly. Parts can be designed right in the assembly and defined by other components, so if they move or change size, the part will automatically update to reflect the change.

Robustness: The Pro/ENGINEER family of products is based on a double precision, nonfaceted solid modeling core. This provides the engineer with the most accurate representation of geometry, mass properties, and interference checking available. Change Management: Powerful change capabilities are inherent with Pro/ENGlNEER full associativity, enabling design-through-manufacturing disciplines to execute their functions in parallel. Tools for parametric data management successfully manage these simultaneous processes and promote an organized, controlled workflow. Hardware Independence: Pro/ENGINEER runs on all of the major UNIX and Windows NT

platforms, maintaining the same look and feel on every system. Users can select the most economical hardware configuration for their needs, and mix and match any combination of platforms. Information can be easily exchanged from one machine to the other, with Pro/ENGINEER managing any architectural differences. CATIA

CATIA- Computer Aided Three-dimensional Interactive Application CATIA is the most powerful multi-platform CAD/CAM/CAE/PLM software package of its

kind in the world. It provides a single platform to design, analyse, and manufacture a product; this

makes the product development faster and easier.

Developed by Dassault Systèmes, the largest player in the global CAD market.

The owner of Solid Works and the ACIS kernel. CATIA is Solid Works’ big brother.

Handles any conceivable modeling task, such as:

o Part modelling o Assembly modelling o Surface modelling o PDM o FEM o Optimization o CAM o Photo rendering o Mechanism simulation o Ergonomic simulation

CATIA V5 Documents

All files created using CATIA V5 are referred to as documents. The basis of most CATIA

V5 documents is the part document. The part document is similar to the *.model file in

CATIA V4. Different CATIA V5 Workbenches generate different types of documents

(extension types). The following is a list of different workbenches and the extension types:

Part Design *.CATPart

Sketcher *.CATPart

Surface Design *.CATPart

Drafting *.CATDrawing

Assembly Design *.CATProduct

GSA *.CATAnalyis

NC *.CATProcess



Material *.CATMaterial

Shape *.CATShape
