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Image Processing Lecture 1 Introduction and Application - Gaurav Gupta - Shobhit Niranjan
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Image Processing Lecture 1 Introduction and Application - Gaurav Gupta - Shobhit Niranjan.

Dec 24, 2015

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Page 1: Image Processing Lecture 1 Introduction and Application - Gaurav Gupta - Shobhit Niranjan.

Image Processing Lecture 1 Introduction and Application-Gaurav Gupta

-Shobhit Niranjan

Page 2: Image Processing Lecture 1 Introduction and Application - Gaurav Gupta - Shobhit Niranjan.

Instructors

Gaurav Gupta Can catch at : B109/Hall-1 mail at: [email protected] gtalk: gauravg.84@GMAIL more information at: http://home.iitk.ac.in/~gauravg Shobhit Niranjan Can catch at : B211/Hall-1 mail at: [email protected] gtalk: shobhitn@GMAIL more information at: http://home.iitk.ac.in/~nshobhit

Page 3: Image Processing Lecture 1 Introduction and Application - Gaurav Gupta - Shobhit Niranjan.

Course Structure

1. Introduction to Image Processing, Application and Prospects (Today)

2. Introduction, Image formation, camera models and perspective geometry

3. Fourier Transform theory , Convolution and Correlation

4. Color, Image enhancement  Techniques5. Binary images: thresholding, moments, topology 

Note: Some topics may not be in order to maintain coherency and running time requirements. (Bare with us …trying to teach first time !!)

Page 4: Image Processing Lecture 1 Introduction and Application - Gaurav Gupta - Shobhit Niranjan.

Today

Image Formation Range Transformations

Point Processing

Reading for this week: Gonzalez & Woods, Ch. 3

Page 5: Image Processing Lecture 1 Introduction and Application - Gaurav Gupta - Shobhit Niranjan.

Image Formation

f(x,y) = reflectance(x,y) * illumination(x,y)Reflectance in [0,1], illumination in [0,inf]

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Sampling and Quantization

Page 7: Image Processing Lecture 1 Introduction and Application - Gaurav Gupta - Shobhit Niranjan.

Sampling and Quantization

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What is an image? We can think of an image as a function, f, from R2 to R:

f( x, y ) gives the intensity at position ( x, y ) Realistically, we expect the image only to be defined over a

rectangle, with a finite range: f: [a,b]x[c,d] [0,1]

A color image is just three functions pasted together. We can write this as a “vector-valued” function:

( , )

( , ) ( , )

( , )

r x y

f x y g x y

b x y

Page 9: Image Processing Lecture 1 Introduction and Application - Gaurav Gupta - Shobhit Niranjan.

Images as functions

Page 10: Image Processing Lecture 1 Introduction and Application - Gaurav Gupta - Shobhit Niranjan.

What is a digital image?

We usually operate on digital (discrete) images: Sample the 2D space on a regular grid Quantize each sample (round to nearest integer)

If our samples are apart, we can write this as:

f[i ,j] = Quantize{ f(i , j ) } The image can now be represented as a matrix of integer values

Page 11: Image Processing Lecture 1 Introduction and Application - Gaurav Gupta - Shobhit Niranjan.

Image processing

An image processing operation typically defines a new image g in terms of an existing image f.

We can transform either the range of f.

Or the domain of f:

What kinds of operations can each perform?

Page 12: Image Processing Lecture 1 Introduction and Application - Gaurav Gupta - Shobhit Niranjan.

Negative

Page 13: Image Processing Lecture 1 Introduction and Application - Gaurav Gupta - Shobhit Niranjan.

Log

Page 14: Image Processing Lecture 1 Introduction and Application - Gaurav Gupta - Shobhit Niranjan.

Image Enhancement

Page 15: Image Processing Lecture 1 Introduction and Application - Gaurav Gupta - Shobhit Niranjan.

Contrast Streching

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Image Histograms

Page 17: Image Processing Lecture 1 Introduction and Application - Gaurav Gupta - Shobhit Niranjan.

Histogram Equalization

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Neighborhood Processing (filtering) Q: What happens if I reshuffle all pixels within

the image?

A: It’s histogram won’t change. No point processing will be affected…

Need spatial information to capture this.

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Programming Assignment #1 Easy stuff to get you started with

Matlab Shobhit will hold your first tutorial

Topics will be from next 2 lectures

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Applications

&

Research Topics

Page 21: Image Processing Lecture 1 Introduction and Application - Gaurav Gupta - Shobhit Niranjan.

Document Handling

Page 22: Image Processing Lecture 1 Introduction and Application - Gaurav Gupta - Shobhit Niranjan.

Signature Verification

Page 23: Image Processing Lecture 1 Introduction and Application - Gaurav Gupta - Shobhit Niranjan.

Biometrics

Page 24: Image Processing Lecture 1 Introduction and Application - Gaurav Gupta - Shobhit Niranjan.

Fingerprint Verification / Identification

Page 25: Image Processing Lecture 1 Introduction and Application - Gaurav Gupta - Shobhit Niranjan.

Fingerprint Identification Research at UNR Minutiae Matching

Delaunay Triangulation

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Object Recognition

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Object Recognition Research

reference view 1 reference view 2

novel view recognized

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Indexing into Databases

Shape content

Page 29: Image Processing Lecture 1 Introduction and Application - Gaurav Gupta - Shobhit Niranjan.

Indexing into Databases (cont’d)

Color, texture

Page 30: Image Processing Lecture 1 Introduction and Application - Gaurav Gupta - Shobhit Niranjan.

Target Recognition

Department of Defense (Army, Airforce, Navy)

Page 31: Image Processing Lecture 1 Introduction and Application - Gaurav Gupta - Shobhit Niranjan.

Interpretation of aerial photography is a problem domain in both computer vision and registration.

Interpretation of Aerial Photography

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Autonomous Vehicles

Land, Underwater, Space

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Traffic Monitoring

Page 34: Image Processing Lecture 1 Introduction and Application - Gaurav Gupta - Shobhit Niranjan.

Face Detection

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Face Recognition

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Face Detection/Recognition Research at UNR

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Facial Expression Recognition

Page 38: Image Processing Lecture 1 Introduction and Application - Gaurav Gupta - Shobhit Niranjan.

Face Tracking

Page 39: Image Processing Lecture 1 Introduction and Application - Gaurav Gupta - Shobhit Niranjan.

Face Tracking (cont’d)

Page 40: Image Processing Lecture 1 Introduction and Application - Gaurav Gupta - Shobhit Niranjan.

Hand Gesture Recognition

Smart Human-Computer User Interfaces Sign Language Recognition

Page 41: Image Processing Lecture 1 Introduction and Application - Gaurav Gupta - Shobhit Niranjan.

Human Activity Recognition

Page 42: Image Processing Lecture 1 Introduction and Application - Gaurav Gupta - Shobhit Niranjan.

Medical Applications

skin cancer breast cancer

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Morphing

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Inserting Artificial Objects into a Scene

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Companies In this Field In India and came to IITK* Sarnoff Corporation Kritikal Solutions National Instruments GE Laboratories Ittiam, Bangalore Interra Systems, Noida Yahoo India (Multimedia Searching) nVidia Graphics, Pune (have high requirements) ADE Bangalore, DRDO

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Links for Self Study and a little Play http://undergraduate.csse.uwa.edu.au/units/2

33.412/

http://www.netnam.vn/unescocourse/computervision/computer.htm

Book: Digital Image Processing, 2nd Edition

by Gonzalez and Woods, Prentice Hall

Page 47: Image Processing Lecture 1 Introduction and Application - Gaurav Gupta - Shobhit Niranjan.

Good Luck !!!