Fast Exhaustive-Search equivalent pattern matching through hierarchical partitioning

Pattern Matching is a fundamental problem in computer vision, and image and video processing. Exhaustive-Search equivalent algorithms yield the same results as exhaustively searching all patterns in the image but significantly faster. In this paper we propose a new exhaustive search equivalent pattern algorithm GHP that generalizes and extends over a number of algorithms that have been widely used and thought of in literature as different algorithms. GHP provides generalized hierarchical partitioning scheme that is applicable to any distance norm and also to additive metrics. We compare GHP with state of art algorithms and show it can be many times faster. We evaluated GHP for 6 different dissimilarity measures.