EECS 4330 - Image Analysis and Computer Vision Course Syllabus
Credits/Contact Hours
Three Credit hours, 3 contact hours per week.
Textbook
R. C. Gonzalez, R. E. Woods, Digital Image Processing, 3rd edition, Prentice Hall.
Course Information
Imaging geometry, image filtering, segmentation techniques, image representation and
description, stereo vision and depth measurements, texture analysis, dynamic vision and motion analysis, matching and recognition.
Prerequisites: EECS 3300
Elective Course
Specific Goals - Student Learning Objectives (SLOs)
The students will be able to
1. To display and implement various image processing algorithms.
2. To design various image filtering techniques including median filtering, and Gaussian
smoothing.
3. To perform various image segmentation techniques and edge detection.
4. To design algorithms for contour and region representations.
5. To devise techniques for stereo vision and depth measurements.
6. To evaluate and measure texture information.
7. To analyze dynamic scenes.
8. To perform feature extraction and object recognition.
Topics
- Image Geometry.
- Image filtering, median filter, Gaussian smoothing.
- Segmentation techniques, edge detection.
- Image representation and description, contour and region representation.
- Stereo vision and depth measurements.
- Texture analysis.
- Dynamic vision and motion analysis.
- Matching and recognition.