Computer Vision is essentially concerned with emulating the process of seeing, naturally manifested in various higher biological systems,1–4 on a computational apparatus, and is consequently part of the Artificial Intelligence field within the sub-category of Machine perception. Seeing has to do with making sense of image data acquired through an optical system and subsequently dealt with at increasing levels of abstraction and association with known facts about the world. The spectrum of interest in Computer Vision ranges from attempting to answer basic questions concerning the functionality of biological vision systems, particularly human, at one end, all the way to enhancing the reliability, speed and cost effectiveness of specific industrial operations, particularly component inspection and vision driven robotic manipulation. The main bulk of interest is in the middle, where the quest for generality pushes interest towards biological vision systems with their demonstrated effectiveness in a wide range of environments, some hostile, whilst the need for economic viability and timeliness in relation to particular application pushes interest towards finding workable algorithms which function reliably at high speed on affordable apparatus.
This paper is addressed, in somewhat tutorial style, at clarifying, by examples of work in the area, the issues surrounding application oriented robotic vision systems, their assumptions, strengths, weaknesses and degree of generality, and at the same time putting them in the context of the overall field of Computer Vision. In addition, the paper points to directions of development which promise to provide powerful industrial vision tools at an acceptable price.