Paper Info
Title
Evaluating Robustness Of Template Matching Algorithms As A Multi-Objective Optimisation Problem
Abstract
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.
Year
DOI
Venue
2014
10.1007/978-3-319-12568-8_4
PROGRESS IN PATTERN RECOGNITION IMAGE ANALYSIS, COMPUTER VISION, AND APPLICATIONS, CIARP 2014
Keywords
Field
DocType
Template matching, robustness evaluation, Multiobjective Optimisation Theory
Template matching,Pattern recognition,Computer science,Algorithm,Robustness (computer science),Artificial intelligence,Distortion
Conference
Volume
ISSN
Citations 
8827
0302-9743
0
PageRank 
References 
Authors
0.34
7
3
Name
Order
Citations
PageRank
José Bernal1203.29
María Trujillo2115.38
Ivan Cabezas381.88