EC861 Image Processing and Computer Vision
Course Name:
EC861 Image Processing and Computer Vision
Programme:
M.Tech(SPML)
Category:
Elective (Ele)
Credits (L-T-P):
(4-0-0) 4
Content:
Overview of image processing systems, image formation and perception, continuous and digital image representation, image quantization, image contrast enhancement, histogram equalization, 2D signals and systems, 2D sampling, linear convolution in 2D, continuous and Discrete Fourier transform in 2D, image filtering in the DFT domain, color representation and display; true and pseudo color image processing, image compression, imaging geometry, model of image degradation/restoration process, texture analysis, motion analysis, geometric camera models, stereopsis, structure from motion, tracking, robot vision, object identification.
References:
Anil K. Jain, Fundamentals of digital image processing, Prentice Hall, 1989.
Rafael C. Gonzalez, Richard E. Woods, Digital Image Processing, 2nd Ed, Prentice Hall, 2002.
Forsth D. A. and Ponce J., Computer Vision: A Modern Approach, Prentice Hall, 2003.
Richard Szeliski, Computer Vision: Algorithms and Applications, Springer, 2010.
Hartley and Zisserman, Multiple Geometry in Computer Vision, Cambridge University Press, 2004.
Department:
Electronics and Communication Engineering(ECE)