Section outline

• Select section Day 1: Introduction and Basic Concepts (7 hours)

  Day 1: Introduction and Basic Concepts (7 hours)

  Collapse all Expand all

  1. Introduction to Digital Image Processing

  • Digital image fundamentals and applications
  • Image acquisition, sampling, and pixel relationships

  2. Image Enhancement Techniques

  • Brightness and contrast adjustment
  • Histogram processing and spatial filtering

  Practical Lab: Image enhancement using Python/MATLAB
• Select section Day 2: Filtering and Segmentation (7 hours)

  Day 2: Filtering and Segmentation (7 hours)

  1. Image Filtering Techniques

  • Convolution, correlation, and noise reduction
  • Edge detection using Sobel, Canny, and Prewitt filters

  2. Image Segmentation

  • Thresholding, region-based, and contour segmentation

  Practical Lab: Implementing filters and segmentation algorithms
• Select section Day 3: Advanced Techniques and Applications (7 hours)

  Day 3: Advanced Techniques and Applications (7 hours)

  1. Feature Extraction and Recognition

  • Feature detection, object recognition, and clustering

  2. Image Transformation and Compression

  • Fourier transform, frequency domain processing, and image compression

  Practical Lab: End-to-end application development for medical imaging or computer vision