SRM UNIVERSITY FACULTY OF ENGINEERING AND TECHNOLOGY SCHOOL OF COMPUTING DEPARTMENT OF CSE COURSE PLAN

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1 SRM UNIVERSITY FACULTY OF ENGINEERING AND TECHNOLOGY SCHOOL OF COMPUTING DEPARTMENT OF CSE COURSE PLAN Course Code : CS0323 Course Title : Digital Image Processing Semester : V Course Time : July Dec 2011 DAY 1 SECTION A B C D E Hour Timing Hour Timing Hour Timing Hour Timing Hour Timing Location : S.R.M.E.C Tech Park Faculty Details SEC NAME OFFICE OFFICE HOUR MAIL ID A,B,C,D,E Dr. D. Malathi Tech Park 8 th Floor Mon - Fri malathid@ktr.srmuniv.ac.in REQUIRED TEXT BOOKS 1. Rafael C. Gonzalez, Richard E. Woods, "Digital Image Processing", 2nd edition, Pearson Education, 2007 REFERENCE BOOKS 2. S.Annadurai, R.Shanmugalakshmi, "fundamentals of Digital Image Processing", Pearson Education, Anil Jain K. "Fundamentals of Digital Image Processing", PHI, William Pratt, "Digital Image Processing", Wiley Interscience, 2nd edition 1991 Web resources

2 Prerequisite : MA02011 Objectives: In this course, students will learn the following topics: Image fundamentals and techniques To learn various Image enhancement, restoration and compression techniques To learn various Image segmentation, representation and description methods Assessment Details Cycle Test I : 10 Marks Cycle Test II : 10 Marks Model Examination : 20 Marks Surprise Test : 05 Marks Attendance : 05 Marks Test Schedule S.No. DATE TEST TOPICS DURATION 1 As per Calendar Cycle Test - I Unit I & II 2 periods 2 As per Calendar Cycle Test - II Unit III & IV 2 periods 3 As per Calendar Model Exam All 5 units 3 Hrs

3 Outcomes Students who have successfully completed this course will have full understanding of the following concepts Course outcome Program outcome To learn about Basic knowledge about Digital image processing An ability to understand the basic concepts of Digital Image Processing Image Enhancement An ability to develop Techniques for Image Enhancement Image Restoration An ability to compress images Image Compression An ability to apply the techniques to segment the images Image Segmentation, Representation and Description An ability to use image processing techniques for suitable applications

4 Detailed Session Plan INTRODUCTION Origin of Digital Image processing - fundamental steps - Components of Image processing system - Visual perception - Light and EM spectrum - Image sensing and acquisition - Image sampling and Quantization - relationship between pixels. Session No. Topics to be covered Time (min) Ref Teaching Method Testing Method 1 2 Origin of Digital Image processing,quiz Fundamental steps in digital image processing Quiz 3 Components of Image processing system Quiz Visual perception Quiz Light and EM spectrum Quiz Image sensing and acquisition 7 Image sampling 8 Image quantization 9 Relationship between pixels. IMAGE ENHANCEMENT Spatial Domain: Gray level transformation - Histogram processing - Arithmetic / Logic operations- Spatial filtering - smoothing filters - sharpening filters Frequency Domain: Fourier transform - smoothing frequency domain filters - sharpening filters - Homographic filtering.

5 10 Gray level transformation, Quiz Histogram processing Arithmetic / Logic operations- Comparative Study Spatial filtering Quiz smoothing filters Quiz Sharpening Filters Quiz, Assignment Fourier Transform Quiz, Group discussion Frequency Domain, Quiz Smoothing Frequency Domain Sharpening Filters Comparative Study Homographic filtering Quiz IMAGE RESTORATION Model of Image degradation/ restoration process - Noise models - mean filters - order statistics - adaptive filters - band reject - bandpass - notch - optimum notch filters - Linear, position invariant degradations - establishing degradation functions - Inverse filtering - Weiner - least square - Geometric mean filters. 21 Model of Image degradation/ restoration process, Noise models 50 1,3 BB Mean Filters Quiz Order Statistics 1,3 Quiz 50 BB Adaptive filtes BB Band Reject, Bandpass, Notch filters and optimum notch filters 50 1,3 Quiz Linear, Position invariant degradations 1,3 Estimating degrading functions Quiz

6 28 29 Inverse and Weiner Filtering Quiz Least square and Geometric mean filters IMAGE COMPRESSION Fundamentals - Image compression models - Information theory - error free compression: variable length - LZW - Bitplane - Lossless predictive coding; Lossy compression : Lossy predictive - transform - wavelet coding; Image compression standards. 30 Fundamentals of image compression 50 1 BB Image compression models 50 1 Information theory 50 1 Quiz 33 Error Free Compression, Variable Length Coding Bitplane coding 50 1 Quiz Lossless Predictive coding Lossy Compression: Lossy predictive coding 50 1 Transform coding 50 1 Quiz Wavelet coding 50 1 Compression standards 50 1 Comparative study IMAGE SEGMENTATION, REPRESENTATION & DESCRIPTION Segmentation: Detection of discontinuities - Edge linking & Boundary detection - Thresholding - region based segmentation Representation & Description: Chain codes - Polygonal approximations - signatures - Boundary segments - Skeletons; Boundary Descriptors - Regional descriptors

7 Segmentation: Detection of discontinuities 50 1 BB, Quiz Edge linking, Boundary detection 50 1 BB Quiz Thresholding 50 1 Region based segmentation 50 1 Objective Type Test Chain codes: Polygonal approximations, Signatures, Boundary segments, Skeletons 50 1 Boundary and Regional Descriptors 50 1 BB Black Board PP Power Point