2014 | OriginalPaper | Chapter
Evaluating Robustness of Template Matching Algorithms as a Multi-objective Optimisation Problem
Authors : Jose Bernal, Maria Trujillo, Ivan Cabezas
Published in: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Publisher: Springer International Publishing
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
Template matching has multiple applications on different problems in computer vision. Image distortions remain as the main challenge that template matching algorithms have to overcome. Thus, measuring robustness of algorithms against distortion conditions is an important task. Moreover, a comparison among template matching algorithms is difficult to achieve due to the lack of a standard evaluation methodology. In this paper, a measurement for quantifying the robustness of template matching algorithms against a single distortion is introduced. In addition, a procedure for comparing template matching algorithms is presented, aiming to become an evaluation standard. The comparison of template matching algorithms is formulated as a Multi-objective Optimisation problem. Experimental evaluation of the proposed procedure, using the robustness coefficient, is conducted by comparing algorithms based on full-search and different similarity measurements.