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Published in:
2009 | OriginalPaper | Chapter
A Template Analysis Methodology to Improve the Efficiency of Fast Matching Algorithms
Authors : Federico Tombari, Stefano Mattoccia, Luigi Di Stefano, Fabio Regoli, Riccardo Viti
Published in: Advanced Concepts for Intelligent Vision Systems
Publisher: Springer Berlin Heidelberg
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Several methods aimed at effectively speeding up the block matching and template matching tasks have been recently proposed. A class of these methods, referred to as exhaustive due to the fact that they optimally solve the minimization problem of the matching cost, often deploys a succession of bounding functions based on a partitioning of the template and subwindow to perform rapid and reliable detection of non-optimal candidates. In this paper we propose a study aimed at improving the efficiency of one of these methods, that is, a state-of-the-art template matching technique known as
Incremental Dissimilarity Approximations
(IDA). In particular, we outline a methodology to order the succession of bounding functions deployed by this technique based on the analysis of the template only. Experimental results prove that the proposed approach is able to achieve improved efficiency.