Syllabus of Shivaji University BE Computer Science and Engineering - ii) Image Processing and Pattern Recognition

Part-II

5 Elective II

Teaching scheme:

Lectures: 3 Hrs/week
Tutorials: 1 hr/week

Examination scheme:

Theory paper: 100 Marks
Term Work: 25 Marks

Section – I

1. Introduction: Digital image processing – problems and applications, Image representation and modeling, 2D systems and necessary mathematical preliminaries. - (4)

2. Image Transforms: 2-D orthogonal and Unitary transforms, 1-D DFT, 2- D DFT, Cosine and Hadamand transforms, Harr and Slant Transforms, KL transforms. - (8)

3. Image Enhancement: Point operations, Histogram modeling, Spatial operations, Transform operations. - (5)

Section – II

4. Image Filtering: Inverse and Wiener filtering, FIR Wiener filters, Filtering using image transforms, smoothing splines and interpolation, least square filters. - (6)

5. Image Analysis: Spatial feature extraction, edge detection, boundary extraction, boundary representation, region representation, moment representation. - (5)

6. Approaches to Pattern Recognition: Pattern vectors & pattern classes, pattern preprocessing, pattern classification methods- statistical approach. Use of decision functions. Clustering techniques, MMD and KNN approaches, Automatic cluster formation, memory network. Approach to pattern Recognition. - (7)

Books:

1. Fundamentals of Digital Image Processing – A.K. Jain (PHI)
2. Introductory Computer Vision and Image Processing – A. Low (MGH)
3. Pattern Recognition Principles – J.T. Tou, R.C.Gonzalez (Addison-Wesley)

Term Work:

It should consist of 8-10 assignments on above topics with emphasis on solving problems on above mentioned topics.