{"id":40,"title":"Image Processing","credit_hour":"3","lecture_hour":"45","outcome":"<!DOCTYPE html>\r\n<html>\r\n<head>\r\n<\/head>\r\n<body>\r\n<ul>\r\n<li>Understand the relevant aspects of digital image representation and their practical implications.<\/li>\r\n<li>Have the ability to design pointwise intensity transformations to meet stated specifications.<\/li>\r\n<li>Understand 2-D convolution, the 2-D DFT, and have the ability to design systems using these concepts.<\/li>\r\n<li>Have a command of basic image restoration techniques.<\/li>\r\n<li>Appreciate the utility of wavelet decompositions and their role in image processing systems.<\/li>\r\n<li>Have an understanding of the underlying mechanisms of image compression.<\/li>\r\n<\/ul>\r\n<\/body>\r\n<\/html>","description":"<!DOCTYPE html>\r\n<html>\r\n<head>\r\n<\/head>\r\n<body>\r\n<p style=\"text-align: justify;\">An introduction to the science of computer vision and image processing. Topics include: point operations, histograms, spatial operations, image rectification, interpolation, affine and other transformations, contrast enhancement, magnification, Fourier image transforms, edge and contour detection, boundary extraction and representation. Focus is mainly placed on the general principles of image processing. Other topics discussed include morphological image processing, wavelets, compression and convolution operations for the tasks of image classification, localization and detection.<\/p>\r\n<\/body>\r\n<\/html>","books":"<!DOCTYPE html>\r\n<html>\r\n<head>\r\n<\/head>\r\n<body>\r\n<ol>\r\n<li><em>Digital Image Processing (3rd Edition)<\/em> Rafael C. Gonzalez, Richard E. Woods<\/li>\r\n<li><em>Fundamentals of Digital Image Processing<\/em> by A. K. Jain<\/li>\r\n<\/ol>\r\n<\/body>\r\n<\/html>","created_at":"2016-09-03 13:01:30","updated_at":"2016-09-03 13:01:30"} Details | Department of Computer Science and Engineering, IUB

CSC 604: Image Processing

Offered Under: M.Sc. in Computer Science (CSC)

Description

An introduction to the science of computer vision and image processing. Topics include: point operations, histograms, spatial operations, image rectification, interpolation, affine and other transformations, contrast enhancement, magnification, Fourier image transforms, edge and contour detection, boundary extraction and representation. Focus is mainly placed on the general principles of image processing. Other topics discussed include morphological image processing, wavelets, compression and convolution operations for the tasks of image classification, localization and detection.

Prerequisites:

CSC 305 + Lab : Object-Oriented Programming

MAT 212 : Probability & Statistics for Science and Engineering

MAT 301 : Ordinary Differential Equations

Course Type	Major
Credit Hour	3
Lecture Hour	45

Expected Outcome(s):

Understand the relevant aspects of digital image representation and their practical implications.
Have the ability to design pointwise intensity transformations to meet stated specifications.
Understand 2-D convolution, the 2-D DFT, and have the ability to design systems using these concepts.
Have a command of basic image restoration techniques.
Appreciate the utility of wavelet decompositions and their role in image processing systems.
Have an understanding of the underlying mechanisms of image compression.

Suggested Books:

Digital Image Processing (3rd Edition) Rafael C. Gonzalez, Richard E. Woods
Fundamentals of Digital Image Processing by A. K. Jain

Grading Policy:

Biweekly Quiz, One Midterm Exam, One Final Exam, Project