How to study Image Processing & Pattern Recognition — Semester VI, Pokhara University BECE

What it covers

Image processing and pattern recognition techniques: image enhancement, filtering, segmentation, feature extraction, and classification, with applications in areas such as medical imaging and computer vision.

Topics worth extra time

1. Digital image fundamentals: sampling, quantisation and pixel relationships
2. Image enhancement in the spatial and frequency domains
3. Image restoration and compression
4. Segmentation, edge detection and morphological operations
5. Feature extraction and pattern recognition basics

How to study it

Experiment with real images using Python (OpenCV, scikit-image): apply filters, histograms and edge detectors and see what changes. Work small numerical examples by hand, such as histogram equalisation on a tiny image.

In the exam

Show calculations on given pixel matrices step by step. Include before/after sketches or diagrams where they explain a technique.

Image Processing & Pattern Recognition notes · All study guides