Machine Vision Tutorial (English Version)

Author: (USA) Snyder et al.
Publisher:
Publication Date: 2005-01-01
Features: This book is an introduction to machine vision, rich in content and easy to understand. It provides all the necessary theoretical tools and demonstrates how to apply them to practical image processing and machine vision systems. The book includes many programming exercises to help students deepen their understanding of the development of practical image processing algorithms. It begins with a review of mathematical principles, then discusses key issues in digital image processing, such as image description and features, edge detection, feature extraction, segmentation of texture and shape, etc. The book also covers topics like image matching, statistical pattern recognition, grammatical pattern recognition, clustering, diffusion, adaptive contours, parametric transformations, and coherence labeling, introducing important applications including automatic target recognition. Continuity and optimization are two recurring themes in the book. It is suitable for senior undergraduate and graduate students in electrical and computer engineering, computer science, and teaching disciplines, as well as for relevant engineering professionals, who will find it highly valuable as a reference. The accompanying CD-ROM includes the software and data used in the book.