An encyclopedia of machine vision, with thorough alphabetized articles on theories and technologies for image processing, modeling, classification, and understanding, is provided in this reference. From epipolar and Euclidian geometry or eigenspace methods to obstacle detection and 3D image integration, these two volumes cover all relevant work done in the field, with an emphasis on foundational concepts.

Most articles are the length of a standard conference paper and describe a well-defined single subject in a concise but thorough way, including the historical background, the main theoretical findings and industrial applications, and a thorough reference section. Furthermore, each article is authored by an expert in the field.

These two volumes are a lot more than a loose compilation of articles. They constitute a monumental effort by a large scientific community to provide systematic terminology for, and organization to, this very active and extensive field of research.

Even though the reference guide has an online version that is kept up to date, the material in the hardcopy is foundational, and so it becomes invaluable to students and practitioners desiring to obtain a well-rounded perspective of computer vision. It is a must have in a machine vision scientist’s library.