Template matching using chaotic imperialist competitive algorithm

Authors:
Haibin Duan;Chunfang Xu;Senqi Liu;Shan Shao
Affiliations:
State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing 100191, China;State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing 100191, China and National Key Laboratory of Science and Technology on Holistic Control, Beihang Univers ...;State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing 100191, China and National Key Laboratory of Science and Technology on Holistic Control, Beihang Univers ...;Shenyang Aircraft Design and Research Institute, Shenyang 110035, China
Venue:
Pattern Recognition Letters
Year:
2010

Citing 1
Cited 3

Template Matching Techniques in Computer Vision: Theory and Practice

Template Matching Techniques in Computer Vision: Theory and Practice

The entire range of Chaotic pattern recognition properties possessed by the Adachi neural network

Intelligent Decision Technologies
A novel evolutionary algorithm inspired by the states of matter for template matching

Expert Systems with Applications: An International Journal
Imperialist competitive algorithm optimized artificial neural networks for UCAV global path planning

Neurocomputing

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Abstract

Image matching plays an important role in feature tracking, object recognition, stereo matching, digital photogrammetry, remote sensing, and computer vision. Imperialist competitive algorithm (ICA) is inspired by imperialistic competition mechanism. In this paper, we present a novel template matching method based on chaotic ICA. Based on the introduction of the principle of ICA, the correlation function used in this approach is proposed. The chaos can improve the global convergence of ICA, and the phenomena of falling into local best solution can be prevented. The detailed process for chaotic ICA-based template matching is also presented in detail. The three typical comparative results show that our proposed chaotic ICA image matching approach is more efficient and effective than the basic ICA.