A Design of the Object Detection System Using the RGA

Seiki Yoshimori; Yasue Mitsukura; Minora Fukumi; Norio Akamatsu

A Design of the Object Detection System Using the RGA

Seiki Yoshimori, Yasue Mitsukura, Minora Fukumi, Norio Akamatsu

Research output: Contribution to conference › Paper › peer-review

Abstract

License plate recognition is very important in an automobile society. However, it is very difficult to do it, because a background and a body color of cars are similar to that of the license plate. Furthermore, the detection of cars in a moving at a very high-speed is difficult to be done. In this paper, we propose a new robust thresholds determination method in the various background by using the real coded genetic algorithm (RGA). By using RGA, the most likely plate colors are decided under various light conditions. First, the average brightness Y values of images are calculated. Next, relationship between the Y value and the most likely plate color thresholds (upper and lower bounds) are obtained by GA to estimate threshold equations by using the recursive least squares (RLS) algorithm. Finally, in order to show the effectiveness of the proposed method, we show simulation examples by using real images, and result rate of detection is 85.0%.

Original language	English
Pages	1227-1231
Number of pages	5
Publication status	Published - 2003 Sep 24
Externally published	Yes
Event	International Joint Conference on Neural Networks 2003 - Portland, OR, United States Duration: 2003 Jul 20 → 2003 Jul 24

Other

Other	International Joint Conference on Neural Networks 2003
Country	United States
City	Portland, OR
Period	03/7/20 → 03/7/24

ASJC Scopus subject areas

Software
Artificial Intelligence

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title = "A Design of the Object Detection System Using the RGA",

abstract = "License plate recognition is very important in an automobile society. However, it is very difficult to do it, because a background and a body color of cars are similar to that of the license plate. Furthermore, the detection of cars in a moving at a very high-speed is difficult to be done. In this paper, we propose a new robust thresholds determination method in the various background by using the real coded genetic algorithm (RGA). By using RGA, the most likely plate colors are decided under various light conditions. First, the average brightness Y values of images are calculated. Next, relationship between the Y value and the most likely plate color thresholds (upper and lower bounds) are obtained by GA to estimate threshold equations by using the recursive least squares (RLS) algorithm. Finally, in order to show the effectiveness of the proposed method, we show simulation examples by using real images, and result rate of detection is 85.0%.",

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AU - Yoshimori, Seiki

AU - Mitsukura, Yasue

AU - Fukumi, Minora

AU - Akamatsu, Norio

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