SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Efficient template matching for multi-channel images
Pattern Recognition Letters
Applying parallel design techniques to template matching with GPUs
VECPAR'10 Proceedings of the 9th international conference on High performance computing for computational science
Adaptive Low Resolution Pruning for fast Full Search-equivalent pattern matching
Pattern Recognition Letters
Level-set-based motion estimation algorithm for multiple reference frame motion estimation
Journal of Visual Communication and Image Representation
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This paper proposes a novel method for fast pattern matching based on dissimilarity functions derived from the Lp norm, such as the Sum of Squared Differences (SSD) and the Sum of Absolute Differences (SAD). The proposed method is full-search equivalent, i.e. it yields the same results as the Full Search (FS) algorithm. In order to pursue computational savings the method deploys a succession of increasingly tighter lower bounds of the adopted Lp norm-based dissimilarity function. Such bounding functions allow for establishing a hierarchy of pruning conditions aimed at skipping rapidly those candidates that cannot satisfy the matching criterion. The paper includes an experimental comparison between the proposed method and other full-search equivalent approaches known in literature, which proves the remarkable computational efficiency of our proposal.