This volume introduces the fundamental concepts and tools involved in the design and implementation of object recognition systems. Divided into three parts, it first introduces the topic and covers the acquisition of images, then details 3-D object reconstruction, modelling and matching, and finally describes typical recognition systems using case studies. Key features include: Extensive literature surveys of state-of-the-art systems Recognition will be essential reading for research scientists, advanced undergraduate and postgraduate students in computer vision, image processing and pattern classification. It will also be of interest to practitioners working in the field of computer vision.
Part A - Introduction and Acquisition Systems: 1. Introduction.- 2. Stereo Matching and Reconstruction of a Depth Map.- Part A - Summary.- Part B - Database Creation and Modeling for 3D Object Recognition: 3. 3-D Object Creation for Recognition.- 4. Object Representation and Feature Matching.- Part B - Summary.- Part C - Vision Systems - Case Studies: 5. Optical Character Recognition.- 6. Recognition by Parts and Part Segmentation Techniques.- 7. 3D Object Recognition Systems.- Part C - Summary: A. Vector and Matrix Analysis.- B. Principal Component Analysis.- C. Optimisation Fundamentals.- D. Differential Geometry - Basic Principles.- E. Spline Theory.- F. Detailed Derivation of Registration Equations.- References.- Index.