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EC-835 Digital Image Processing
Campus College of E&ME
Programs PG
Session Fall Semester 2016
Course Title Digital Image Processing
Course Code EC-835
Credit Hours 03
Pre-Requisutes Digital Image Processing by Rafael C. Gonzalez, Richard E. Woods, Addison Wesley, 3rd Ed. 2008.
  • Basic knowledge about linear algebra, matrices and complex variables.
  • Concepts related to signals and systems and digital sig
Course Objectives
  • To develop thorough understanding of digital image processing fundamentals.
  • To explore the properties of discrete transforms and their importance with respect to image processing.
  • To study various image enhancement techniques in spatial and frequency domains, fundamentals of image compression, introduction to color image processing, wavelets and morphological image processing.
  • To have a basic understanding of some topics of machine learning to combine these ideas with image processing techniques to produce good projects.
Detail Content Grading:
Sessional Exams: 25%.
Quizzes (4-6): 10%.
Computer and numerical assignments: 10%.
Final Project: 15%.
Final Exam: 40%.


Quizzes:
Ten-minute surprise quizzes will be given periodically.

Computer Assignments & Project:
For computer assignments, sharing of programming tips and discussing general concepts is allowed. Collaborating on program writing is not. The term-project will be conducted in groups. One to three students can form a group. It is very important to have hands on image processing algorithms. Almost 25% marks are directly related to it inform of computer assignments and projects etc. The project will be monitored throughout the semester on periodic basis and marks will be assigned accordingly.

Topical Outline:
  • Introduction to Image processing
  • Image processing Fundamentals
  • Image Enhancement & Restoration
  • Morphological operations
  • Feature extraction (edges, corners)
  • Segmentation
  • Texture analysis
  • Wavelets
  • Introduction to Machine Learning and basic types of classifiers, Performance parameters for evaluation
Text/Ref Books
  • Digital Image Processing Using Matlab by Rafael C. Gonzalez and Richard E. Woods, Pearson Education, 2009.
  • Digital Image Processing by Kenneth R. Castleman, Prentice Hall International Edition, 1996.
  • http://www.imageprocessingplace.com/
Time Schedule Fall 2015
Faculty/Resource Person