PARTICLE SWARM OPTIMIZATION FOR TEMPLATE MATCHING(International Workshop on Advanced Image Technology 2007)
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概要
- 論文の詳細を見る
In this paper we propose an approach, which uses Particle Swarm Optimization (PSO) for template matching problems. Template matching is an important technique to investigate similarities between two patterns, predefined patterns (template) and target patterns. Template matching is also useful for detection of an object by determining angle, position and magnification ratio in an image. For detection of a two dimensional object, four parameters (angle, x-coordinate, y-coordinate and magnification ratio) have to be optimized in template matching. However, the search space consisting of these four parameters is so huge that it takes a lot of calculations to investigate all searching points. PSO is one of the new optimization algorithms which is categorized as an evolutionary algorithm, and based on an analogy of the movement of flight of a flock of birds. Each bird (called aparticle in PSO) represents the searching point in search space. In this research, each particle has four dimensional vectors and updates either two known PSO algorithms (inertia weight approach or constriction coefficient approach). We apply PSO to the template matching problem, and compare the PSO based algorithm to the simple Genetic Algorithm (GA) in two kinds of two dimensional images. Experimental results show that the PSO based algorithm is able to obtain accurate results and locate an optimal solution significantly faster than GA. Besides, the PSO approaches outperform in terms of processing cost.
- 社団法人電子情報通信学会の論文
- 2007-01-02
著者
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Nagao Tomoharu
Department of Information Media and Environment Graduate School of Environment and Information Scien
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Ando Hiroshi
Department of Internal Medicine, Saga Prefectural Hospital, Kohseikan
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Nagao Tomoharu
Department Of Information Media And Environment Graduate School Of Environment And Information Scien
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Ando Hiroshi
Department Of Information Media And Environment Graduate School Of Environment And Information Scien
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Ando Hiroshi
Department Of Environmental Health And Toxicology Tokyo Metropolitan Institute Of Public Health
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