Digital image processing

Seminar Report on

Digital Image Processing

Submitted by

Trishna Pattanaik

< Regd. No.: 1301229183 >

Project Report submitted in partial fulfillment of the

requirements for the award of the degree of

B.Tech. in Computer Science & Engineering under

Biju Pattnaik University of Technology (BPUT)

2016-2017

Under the Guidance of

Surajit Mohanty

HOD Dept. of CSE

Department of Computer Science & Engineering

DRIEMS Tangi, Cuttack-745022

CERTIFICATE

This is to certify that the project Digital Image Processing presented

by Trishna Pattanaik bearing Registration No. 1301229183 of

Department of Computer Science and Engineering in DRIEMS,

Cuttack has been completed successfully.

This is in partial fulfillment of the requirements of Bachelor Degree in

Computer Science and Engineering under Biju Pattnaik University of

Technology, Rourkela, Orissa.

I wish her success in all future endeavors.

Prof. Surajit Mohanty Prof. Surajit Mohanty Head of the Department Guide Computer Science & Engineering Computer Science & Engineering

Date: 19th March 2016 Date: 19th March 2016

ACKNOWLEDGEMENT

I express my sincere gratitude to Prof. Surajit Mohanty of Computer

Science and Engineering for giving me an opportunity to accomplish

seminar on the project. Without his active support and guidance, this

seminar would not have been successfully completed.

Trishna Pattanaik Department of Computer Science & Engineering Regd.No.- 1301229183

Digital Image Processing

ABSTRACT

Digital image processing (dip) methods stems for two principal application areas: improvement of pictorial information for human interpretation and processing of image data for storage, transmission and representation for autonomous machine perception. Thus, the objectives of the topic are: to define the scope of the field, to give a historical perspective of the origins of this field, to give the idea of the state of the art in dip by examining some of the principal areas in which it is applied, to discuss briefly the principal approaches used in dip and to give an overview of the components contained in a typical general-purpose image processing system. Signature of the Guide Signature of the Student

Name : Prof. Surajit Mohanty Name : Trishna Pattanaik

Date : 19th March 2016 Regn. No : 1301229183

Semester : 6th

Branch : CSE

Section : C

Date : 19th March 2016

TABLE OF CONTENTS

CHAPTER NO. TITLE PAGE NO.

CERTIFICATE i

ACKNOWLEDGEMENT ii

ABSTRACT iii

LIST OF FIGURES v

1. INTRODUCTION 1

1.1 What is digital image processing? 1

1.2 The origins of Digital Image Processing 1

1.3 Fundamental steps for Digital Image Processing 2

2. DIGITAL IMAGE FUNDAMENTALS 4

2.1 Image Acquisition 4

2.2 Image Enhancement 5

2.3 Image Restoration 6

3. COLOR IMAGE PROCESSING 13

5.1 Pseudocolor Image Processing 13

5.2 Full-color Image Processing 13

4. MULTIRESOLUTION & MORPHOLOGICAL 14

IMAGE PROCESSING

4.1 Wavelets & Multiresolution Processing 14

4.2 Morphological Image Processing 15

5. IMAGE SEGMENTATION 16

6. COMPRESSION & REPRESENTATION 17

6.1 Image Compression 17

6.2 Representation & Description 18

6.3 Object Recognition 20

7. FIELDS OF APPLICATION 21

CONCLUSION 23

REFERENCES 24

LIST OF FIGURES

Figure1.1: A digital picture produced in 1921 from a coded tape by a telegraph printer with

special type faces.

Figure 1.2: A digital picture made in 1922 from a tape punched after the signals had crossed

the Atlantic twice.

Figure1.3: The first picture of the moon by a U.S. spacecraft Ranger 7 took this image on

July 31, 1964 at 9:09 A.M. EDT about 17 minutes before impacting the lunar surface.

Figure 1.4: Fundamental steps in digital image processing.

Figure 2.1: Single Imaging Sensor

Figure 2.2: Combining a single sensor with motion to generate a 2-D image.

Figure 2.3: Line Sensor

Figure 2.4: (a) Image acquisition using a linear sensor strip.

(b) Image acquisition using a circular sensor strip.

Figure 2.5: Array Sensor

Figure 2.6: An example of the digital image acquisition process.

Figure 2.7: Some basic gray-level transformation functions used for image enhancement.

Figure 2.8: Comparing lowpass filters.

Figure 2.9: Comparing highpass filters.

Figure 2.10: Noise Examples.

Figure 2.11: Noise removal examples.

Figure 3.1: Result of density slicing into 8 colors on an image of Picker Thyroid Phantom.

Figure 3.2: Pseudocolor enhancement by using the gray level to color transformation.

Figure 3.3: A full-color image and its various color space components.

Figure 4.1: A pyramidal image structure.

Figure 4.2: Erosion to remove image components.

Figure 4.3: Dilation of sample text.

Figure 6.1: Computer Generated 256 X 256 X 8 bit images with (a) coding redundancy

(b) spatial redundancy (c) irrelevant information.

Figure 7.1: Images of the Crab Pulsar (in the centre of images) covering the EM spectrum.

Figure 7.2: A Fractal Image.

v

CHAPTER 1

INTRODUCTION

1.1 WHAT IS DIGITAL IMAGE PROCESSING?

An image may be defined as a two-dimensional function f(x, y), where x and y are spatial

(plane) coordinates and the amplitude of f at any pair of coordinates (x, y) is called the intensity

or gray level of the image at that point. When x, y and the amplitude values of f are all finite,

discrete quantities, we call the image a digital image. The field of digital image processing

refers to processing digital images by means of a digital computer. Note that a digital image is

composed of a finite number of elements, each of which has a particular location and value.

These elements are referred to as picture elements, image elements, pels, and pixels.

Digital image processing encompasses processes whose inputs and outputs are images and

in addition, encompasses processes that extract attributes from images up to and including the

recognition of individual objects. The processes of acquiring an image of the area containing

the text, preprocessing that image, extracting (segmenting) the individual characters,

describing the characters in a form suitable for computer processing, and recognizing those

individual characters are in the scope of what we call digital image processing [2].

1.2 THE ORIGINS OF DIGITAL IMAGE PROCESSING

One of the first applications of digital images was in the newspaper industry, when pictures

were first sent by submarine cable between London and New York. Introduction of the Bartlane

cable picture transmission system in the early 1920s reduced the time required to transport a

picture across the Atlantic from more than a week to less than three hours. The printing method

used to obtain figure 1.1 was abandoned toward the end of 1921 in favor of a technique based

on photographic reproduction made from tapes perforated at the telegraph receiving terminal.

Figure1.1: A digital picture produced in 1921 from a coded

tape by a telegraph printer with special type faces.

1

Figure 1.2 shows an image obtained using this method. The improvements over figure 1.1 are

evident, both in tonal quality and in resolution.

Figure 1.2: A digital picture made in 1922 Figure1.3: The first picture of the moon by a U.S. spacecraft

from a tape punched after the signals had Ranger 7 took this image on July 31, 1964 at 9:09 A.M. EDT

crossed the Atlantic twice. about 17 minutes before impacting the lunar surface.

Although the examples just cited involve digital images, they are not considered digital

image processing results in the context of our definition because computers were not involved

in their creation. The first computers powerful enough to carry out meaningful image

processing tasks appeared in the early 1960s. Figure 1.4 shows the first image of the moon

taken by Ranger 7 on July 31 1964 at 9:09 A.M.Eastern Daylight Time (EDT), about 17

minutes before impacting the lunar surface. From the 1960s until the present, the field of image

processing has grown vigorously. In addition to applications in medicine and the space

program, digital image processing techniques now are used in a broad range of applications.

1.3 FUNDAMENTAL STEPS FOR DIGITAL IMAGE PROCESSING

It is helpful to divide the material covered in the following chapters into the two broad

categories: methods whose input and output are image