Teaching
CSPE77: Image Processing
B. Tech. 5th Semester (2020-21)
Dr. G. K. Verma
Course Learning Objectives
Image Processing is a major course in the computer science major, designed to teach students the fundamentals of digital image processing on the computer. The primary objective of this course is to introduce students to basic principles of digital images, image data structures, and image processing algorithms. Emphasis is on the general principles of image processing. Students learn to apply material by implementing and investigating image processing algorithms in Matlab and optionally on Android mobile devices.
Course outcomes
Acquire the fundamental concepts of a digital image processing system
Apply knowledge of various mathematical tools used for 1D and 2D signal analysis and processing
Analyze 2D signals in the spatial and frequency domain.
Design and implement algorithms for digital image processing operations.
Ability to apply image processing techniques to solve various real time problems.
Grading
Participation: 10 percent
Assignments/ Quiz/ project: 20 percent
Midterm exam: 30 percent
Final exam: 50 percent
Instructional Format
The course will be taught in ''online classroom'' format. You may be provided a pre-recorded lectures, edited into shorter topical modules, and supplemented by quiz questions for reinforcement. Lecture videos and quizzes are released in due time during the semester. You must complete all lectures and quizzes to receive full credit. Students are expected to attend online lectures regularly.
Class Schedule (tentative)
The tentative schedules of the lectures are given below. Please check back on this page regularly for the most up-to-date class schedule.
Popular Textbooks and Reading Material Links
Textbooks:
R. C. Gonzales, R. E. Woods, "Digital Image Processing", 4th Edition, Pearson, 2018
William K. Pratt, "Introduction to Digital Image Processing", CRC Press, 2013
Software-Centric Textbooks:
R. C. Gonzales, R. E. Woods, S. L. Eddins, "Digital Image Processing using MATLAB", 2nd Edition, Gatesmark Publishing, 2009
A. Kaehler, G. Bradski, "Learning OpenCV 3", O'Reilly Media, 2017
Journals and Conference Proceedings:
IEEE Transactions on Image Processing (TIP)
IEEE International Conference on Image Processing (ICIP)
IEEE Computer Vision and Pattern Recognition (CVPR)
COURSERA
https://www.coursera.org/courses?query=image%20processing
NPTEL
https://nptel.ac.in/courses/117/105/117105079/
https://nptel.ac.in/courses/117/105/117105135/
SWAYAM
https://swayam.gov.in/nd1_noc19_cs58/preview