Foundations of Computer Vision: Computational Geometry, Visual Image Structures, and Object Shape Detection

Foundations of Computer Vision introduces the fundamentals of computer vision (CV) with a focus on extracting useful information from digital images and videos. Including a wealth of methods used in detecting and classifying image objects and their shapes, this book applies a trio of tools (computational geometry, topology, and algorithms) in solving CV problems, shape tracking in image object recognition, and detecting the repetition of shapes in single images and video frames. Computational geometry provides a visualization of topological structures such as neighborhoods of points embedded in images, while image topology supplies us with structures useful in the analysis and classification of image regions. Algorithms provide a practical step-by-step means of viewing image structures.

Implementations of CV methods in MATLAB, classification of chapter problems with the symbols, and its extensive glossary of key words, examples, and connections with the fabric of CV make the book a resource for advanced undergraduate and first-year graduate students in engineering, computer science, and applied mathematics.