Important applications are described, including automatic target recognition. They also discuss image matching, statistical pattern recognition, syntactic pattern recognition, clustering, diffusion, adaptive contours, parametric transforms, and consistent labeling. The authors begin with a review of mathematical principles and go on to discuss key issues in image processing such as the description and characterization of images, edge detection, feature extraction, segmentation, texture, and shape. A key feature is the inclusion of many programming exercises that give insights into the development of practical image processing algorithms. It provides all the necessary theoretical tools and shows how they are applied in actual image processing and machine vision systems. This book is an accessible and comprehensive introduction to machine vision. It will also be a useful reference for practitioners.

The book is aimed at graduate students in electrical engineering, computer science, and mathematics. Aimed at graduate students in electrical engineering, computer science, and mathematics, the book will be a useful reference for professionals as well. A key feature is the inclusion of many programming exercises giving insights into the development of practical image processing algorithms. Providing all the necessary theoretical tools, this comprehensive introduction to machine vision shows how these tools are applied in actual image processing and machine vision systems.

Robert beckowitz no sensor