A Comparative Study of Sophisticated High-Speed Pattern Matching Systems for Industrial Applications

摘要

Pattern matching is an important task in industrial applications of computer vision. A variety of different approaches to the pattern matching problem has been proposed in the literature. In this paper we provide an experimental evaluation of three different matching algorithms, namely a feature consensus matching algorithm, an interpretation tree based algorithm and a commercially available pattern matching tool. The systems were chosen to cover a range of matching techniques as well as a large field of possible applications. Both artificially created test images and image sequences of 'real-world' matching problems have been applied to indicate the range of feasible applications to any of the three matching system. The algorithms are investigated with respect to matching speed, accuracy and robustness.