Image Analysis and Processing

Type: Fundamental
Credits: 5
Coefficient: 3
Target Audience: 4th Year AI Engineer

1. Instructor Information

  • Lecturer: Dr. Anouar Khaldi
  • Contact: khaldi.anouar@univ-ouargla.dz
  • Office Hours:
    • Saturday: 08:00 am – 04:00 pm
    • Sunday: 08:00 am – 10:00 am
    • Monday: 01:00 pm – 05:00 pm

2. Course Description

This course provides a solid foundation in Image Analysis and Processing, highlighting its essential role in modern science. Students will explore theoretical concepts and practical applications within the field of artificial vision.

3. Learning Objectives

By the end of this course, students will be able to:

  • Understand digital image representation and grayscale/color models.
  • Compute and interpret image histograms and cumulative distribution functions.
  • Apply histogram-based enhancement techniques such as contrast stretching and histogram equalization.
  • Perform image thresholding and basic segmentation.
  • Implement spatial filtering (smoothing, sharpening) using convolution.
  • Analyze and process images programmatically using Python.

4. Prerequisites

  • Foundations of Python programming.
  • Basic linear algebra.
  • Basic probability and statistics.

5. Evaluation & Assessment

  • Continuous Evaluation (40%): Quiz and class presentation.
  • Final Exam (60%): Comprehensive examination.
  • Success Threshold: A final grade of at least 10/20 is required.