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Proceedings Paper

A fusion algorithm of template matching based on infrared simulation image
Author(s): Ruiheng Zhang; Chengpo Mu; Xiang Gao; Kai Liu; Yingcun Ma
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Paper Abstract

Template matching algorithm is one of the important image-based Automatic Target Recognition methods. Traditional normalized cross correlation (NCC) algorithm used in infrared image matching has a strong antinoise performance but low computing speed. Meanwhile, although sequential similarity detection algorithm (SSDA) performs a shorter time than NCC, it has lower accuracy. In order to solve the low target recognition rate and slow speed of infrared image recognition problems, a new matching algorithm based on infrared image is presented, which integrates the advantages of two methods. The fusion algorithm improves the matching speed and reduces the probability of matching error. The experimental results confirm that the proposed approach has higher efficiency and accuracy in infrared image matching than original algorithms. Comparing with NCC and SSDA, it shortens large recognition time and enhances the right matching ratio respectively. In addition, the improved algorithm is real-time and robust against noise. It is significant to the research and development of automatic target recognition technology for different kinds of real-time detection system.

Paper Details

Date Published: 29 August 2016
PDF: 5 pages
Proc. SPIE 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016), 1003307 (29 August 2016); doi: 10.1117/12.2245095
Show Author Affiliations
Ruiheng Zhang, Beijing Institute of Technology (China)
Chengpo Mu, Beijing Institute of Technology (China)
Xiang Gao, Beijing Institute of Technology (China)
Kai Liu, Beijing Institute of Technology (China)
Yingcun Ma, Beijing Institute of Technology (China)


Published in SPIE Proceedings Vol. 10033:
Eighth International Conference on Digital Image Processing (ICDIP 2016)
Charles M. Falco; Xudong Jiang, Editor(s)

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