Course Code & Number
CMPE 362
Course Title
Digital Image Processing
Credit Hours/ ECTS Credits
(3+0+0) 3 TEDU Credits, 5 ECTS Credits
Mode of Delivery:
Face-to-face
Language of Instruction:
English
Pre-requisite / Co-requisite:
Pre-requisites: MATH 203
Co-requisites: NONE
Catalog Description
Image model sampling and quantization. Basic relationships between pixels and image geometry. Two-dimensional Fourier transforms. Image enhancement. Spatial and frequency domain methods. Image restoration. Image segmentation.
Course Objectives
The objective of this course is to provide effective skills for developing and applying image processing methods and tools to obtain significant information from images.
Course Learning Outcomes
Upon succesful completion of this course, a student will be able to
1. Describe the basic theory of image processing
2. Examine binary and color images using image processing tools
3. Analyze and apply image enhancement methods in spatial and frequency domain
4. Analyze and apply image segmentation methods
5. Analyze and apply algorithms to extract significant information from images
6. Develop solution methods for image processing problems using the state of the art
Learning Activities and Teaching Methods:
Telling/Explaining
Discussion/Debate
Questioning
Reading
Demonstrating
Problem Solving
Collaborating
Think-Pair-Share
Others
Assessment Methods and Criteria:
Test / Exam
Quiz
Others
Assessment Methods and Criteria Others:
Recommended Reading
1. Computer Vision: Algorithms and Applications by R. Szeliski, Springer, 2010. (electronic draft available)
2. Computer Vision by L. G. Shapiro and G. C. Stockman, Prentice Hall, 2001.
Required Reading
1. Digital Image Processing (3rd Edition) by Rafael C. Gonzalez and Richard E. Woods
Grading
Assignments - 45%
Midterm - 20%
Final Exam - 30%
Class participation - 5%
Learning Activities and Teaching Methods Others:
Course & Program Learning Outcome Matching: