Image Analysis and Machine Vision

  • Created: 2015-10-18
  • 1712
Name:Image Analysis and Machine Vision
No.:S081101ZJ004Semester:Autumn
Hour:40Credit:2.0
Teacher:Wang, Weiqiang
Introduction:
 

Aims and Purposes: The course is an introductory course for computer vision, and it focuses on introducing the essential techniques and principle of digital image analysis and processing, as well as the usage of image toolbox and other related toolbox in Matlab programming language. It is expected that a student learning the course can grasp the related techniques, basic theory , and the skill of using Matlab to implement their ideas, especially image processing toolbox, so that he can build a solid foundation for the further learning of computer vision.

Prerequisite: Advanced Mathematics, linear algebra, probability theory

Content:
 
Chapter 1. Matlab and image processing toolbox
Chapter 2. Spatial filtering
Chapter 3. Frequency domain processing
Chapter 4. Image restoration
Chapter 5. Color image processing
Chapter 6. Wavelet and Pyramid decomposition
Chapter 7. Morphological image processing
Chapter 8. Image segmentation
Material:
 
References:
 

1. Rafael C. Gonzalez, Richard E. Woods, "Digital image processing", publishing house of electronics industry, Second edition, 2009.8

2. Rafael C. Gonzalez, Richard E. Woods, Steven L. Eddins, "Digital image processing Using MATLAB", publishing house of electronics industry, First edition, 2006.5