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CPE
433
Computer Vision
This course is concerned with the computer acquisition and analysis of image data. Computer vision is the construction of explicit meaningful descriptions of physical objects or other observable phenomena from images. The emphasis is on physical, mathematical, and information-processing aspects of the vision. Topics to be covered include image formation, edge detection and segmentation, convolution, image enhancement techniques, extraction of features such as color, texture, and shape, object detection, 3-D vision, and computer vision system architectures and applications.
Prerequisites:
0610385,0612207
0612433
(3-0-3)

Credits and Contact Hours

3 credits, 43 hours

Course Instructor Name

Dr. Ahmed Nasrallah

Textbook

Computer Vision: Algorithms and Applications, 2nd ed. 2022 Richard Szeliski

Digital Image Processing 4th Edition, 2017. Rafael Gonzalez, Richard Woods

Catalog Description

This course is concerned with the computer acquisition and analysis of image data. Computer vision is the construction of explicit meaningful descriptions of physical objects or other observable phenomena from images. The emphasis is on physical, mathematical, and information-processing aspects of the vision. Topics to be covered include image formation, edge detection and segmentation, convolution, image enhancement techniques, extraction of features such as color, texture, and shape, object detection, 3-D vision, and computer vision system architectures and applications.

Prerequisite

CpE-207 and EE-385

Specific Goals for the Course

Upon successful completion of this course, students will be able to:

Understand the fundamental concepts of image formation and the processes involved in capturing and representing visual information using computers. (Student Outcomes: 1)

Understand the basic elements of digital signal processing and Fourier transforms with applications. (Student Outcomes: 1)

Gain proficiency in techniques for edge detection and segmentation, essential for isolating and identifying distinct objects within an image. (Student Outcomes: 1, 6)

Demonstrate a comprehension of convolution and its applications in image processing, including filtering and feature extraction. (Student Outcomes: 1, 6)

Apply various image enhancement techniques to improve the quality and clarity of visual information in images. (Student Outcomes: 1, 6)

Master the extraction of features such as color, texture, and shape from images, and understand their significance in computer vision applications. (Student Outcomes: 1, 6)

Develop the skills to detect and recognize objects in images using algorithms and methods discussed in the course. (Student Outcomes: 1, 6)

Topics to Be Covered

Introduction to Computer Vision

Image Formation

Image Enhancement

Image Filtering and Convolution

Image Segmentation

Feature Extraction

Object Detection

3-D Vision

Computer Vision System Architectures

Applications of Computer Vision

Challenges and Future Trends