Template matching using chaotic imperialist competitive algorithm

被引：70

作者：

Duan, Haibin ^{[1
]}

Xu, Chunfang ^{[1
,2
]}

Liu, Senqi ^{[1
,2
]}

Shao, Shan ^{[3
]}

机构：

[1] Beihang Univ, State Key Lab Virtual Real Technol & Syst, Beijing 100191, Peoples R China

[2] Beihang Univ, Natl Key Lab Sci & Technol Holist Control, Beijing 100191, Peoples R China

[3] Shenyang Aircraft Design & Res Inst, Shenyang 110035, Peoples R China

来源：

PATTERN RECOGNITION LETTERS | 2010年 / 31卷 / 13期

关键词：

Image matching; Imperialist competitive algorithm (ICA); Chaotic; Normalized cross-correlation (NCC);

D O I：

10.1016/j.patrec.2009.12.005

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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. (C) 2009 Elsevier B.V. All rights reserved.

引用

页码：1868 / 1875

页数：8