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DIGITAL IMAGE PROCESSING & ANALYSIS (4 credits course)
L-T-P: 3-0-2
Objective of the course:
The course is to provide knowledge with hand-on lab training about the fundamentals of digital image processing and analysis including the topics: image enhancement and filtering in spatial and frequency domain, image transformations, image restoration, image compression, image segmentation, morphological image processing, color image processing, image features extraction, and applications of image processing and analysis in real world scenarios.
The course will help in providing both theory and ability to implement and evaluate different digital image processing and analysis techniques for wide range of applications. The last module will be on the recent methods and research advancement in topics related to digital image processing and techniques.
Course Contents:
Digital image processing techniques for enhancement, compression, restoration, registration, reconstruction, and analysis. Image Enhancement in Spatial Domain: Gray Level Transformation, Histogram Processing, Spatial Filters; Image Transforms: Fourier Transform, Other Transforms; Image Enhancement in Frequency Domain; Colour Image Processing; image restoration; Image Registration: Rigid/Non-Rigid Transformations; Image Compression; Image Segmentation: edge detection, Hough transform, region based segmentation; Morphological operators; Representation and Description; Features based matching and Bayes classification; Introduction to some computer vision techniques;
Suggested texts and reference materials (If any)
1. Digital lmage Processing, R. C. Gonzalez and R. E Woods (Pearson).
2. Fundamentals of Digital lmage Processing, A. K. Jain (Prentice-Hall India)
3. Digital Picture Processing, A. Rosenfeld and A. Kak, volumes 1 & 2, (Academic Press)
4. Principles of Digital Image Processing: Core Algorithms, W. Burger and M. J. Burge (Springer)
Assessment Criteria:
Mid-Semester Written Exam:20
Homeworks: 5
Quizzes: 10
Hands-on Project /Lab Assignments: 25
Research Project: 10
End-Semester Written Exam:30
Course Instructor:
Dr. Puneet Goyal, Faculty, IIT Ropar
Resources:
Visit http://www.iitrpr.ac.in/moodle/course/view.php?id=0617
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