Fast and accurate vision-based pattern detection and identification

Abstract

Fast pattern detection and identification is a fundamental problem for many applications of real-time vision systems. The desirable characteristics for a solution are that it takes little computation, localizes a pattern robustly and with high accuracy, and can identify a large number of unique pattern identifiers so that many patterns can be tracked within a field a view. We will present a system that can accurately track a broad class of patterns both accurately and quickly, when using a suitable low level vision system that can return calibrated coordinates of regions in a image. Both pattern design and the detection algorithm are considered together to find a solution meeting the above criteria. Along the way, assumptions are verified to make informed choices without relying on guesswork, and allowing similar systems to be designed on a solid experimental and statistical basis.