EC769 Computer Vision and Image Understanding

Course Name: 

EC769 Computer Vision and Image Understanding

Programme: 

M.Tech(SPML)

Semester: 

Second

Category: 

Programme Core (PC)

Credits (L-T-P): 

(3-0-2) 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. Image processing domains - segmentation, enhancement, compression, registration 

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.
Scott E Umbaugh, Digital Image Processing and Analysis: Computer Vision and Image Analysis, CRC Press, 2024.
Nazmul Siddique, Mohammad Shamsul Arefin, Md Atiqur Rahman Ahad, M. Ali Akber Dewan, Computer Vision and Image Analysis for Industry 4.0, Chapman and Hall/CRC 2023.

Department: 

Electronics and Communication Engineering(ECE)
 

Contact us

Prof. Ramesh Kini M.
Professor and Head,
Department of ECE, NITK, Surathkal,
P. O. Srinivasnagar,
Mangalore - 575 025 Karnataka, India.

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