Course

Unit I

Introduction and Fundamentals of Image Processing: Origins of Digital Image Processing – Examples – Fundamental Steps in Digital Image Processing – Elements of Visual Perception – A Simple Image Formation Model – Basic Concepts in Sampling and Quantization

Unit II

Representing Digital Images-Zooming and Shrinking Digital Images – Some Basic Relationships between Pixels – Linear and Nonlinear Operations – Connectivity and Relations between Pixels- Simple Operations- Arithmetic, Logical, Geometric Operations.

Unit III

Image Enhancement in the Spatial Domain and Frequency Domain: Some Basic Gray Level Transformations – Histogram Processing – Basics of Spatial Filtering – Smoothing Filters-Mean, Median, Mode Filters – Edge Enhancement Filters – Sobel, Laplacian, Robert, Prewitt filter, Contrast Based Edge Enhancement Techniques.

Unit IV

Design of Low Pass Filters – High Pass Filters- Edge Enhancement – Smoothening Filters in Frequency Domain. Butter Worth Filter, Homomorphic Filters in Frequency Domain-Comparative Study of Filters in Frequency Domain and Spatial Domain.

Unit V

Edge Detection – Line Detection – Curve Detection – Edge Linking and Boundary Extraction – Thresholding Algorithms- Region Based Segmentation – Region Growing – Connected Components Labeling – Region Growing and Region Adjacency Graph (RAG), Split and Merge Algorithms – Morphology – Dilation, Erosion, Opening and Closing.

Course Outcomes

TEXTBOOKS:

1. Rafael C. Gonzalez and Richard E. Woods, ”Digital Image Processing”, Third Edition, Addison Wesley, 2007.

REFERENCES

1. Arthur R. Weeks, Jr., “Fundamentals of Electronic Image Processing”, First Edition, PHI,1996.
2. Milan Sonka, Vaclav Hlavac and Roger Boyle, ”Image processing, Analysis, and Machine Vision”, Third Edition, Vikas Publishing House, 2007.