• The KIPS Transactions:PartB
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• v.16B no.4
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• pp.289-298
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• 2009

Active Contour Model, that is, Snake algorithm is effective for detection and tracking the objects. However, this algorithm has some drawbacks; numerous parameters must be designed(weighting factors, iteration steps, etc.), a reasonable initialization must be available and moreover suffers from numerical instability. Therefore we propose a novel Energy Corrected Snake(ECS) algorithm which improved on external energy of Snake algorithm for detection and tracking the moving object more effectively. The proposed algorithm uses the difference image, getting when the object is moving. It copies four direction images from the difference image and performs the accumulating compute to erasing image noise, so that it gets external energy steadily. Then external energy united with contour that is computed by internal energy. Consequently we can detect and track the moving object more speedily and easily. To show the effectiveness of the proposed algorithm, we experiment on 3 situations. The experimental results showed that the proposed algorithm outperformed by 6$\sim$9% of detection rate and 6$\sim$11% of tracker detection rate compared with the Snake algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.5
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• pp.1052-1061
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• 2003

In this paper, we propose the car plate recognition using SOM algorithm and describe the parking control system using the proposed car plate recognition. The recognition of car plate was investigated by means of the SOM algorithm. The morphological information of horizontal and vertical edges was used to extract a plate area from a car image. In addition, the 4-direction contour tracking algorithm was applied to extract the specific area, which includes characters from an extracted plate area. The extracted characteristic area was recognized by using the SOM algorithm. In this paper, 50 car images were tested. The extraction rate obtained by the proposed extraction method showed better results than that from the color information of RGB and HSI, respectively. And the car plate recognition using SOM algorithm was very efficient. We develop the parking control system using the proposed car plate recognition that shows performance improvement by the experimental results.

• The KIPS Transactions:PartB
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• v.9B no.3
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• pp.359-368
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• 2002

In this paper, we propose effective boundary line extraction algorithm for moving objects by matching error image and moving vectors, and fast tracking algorithm for moving object by partial boundary lines. We extracted boundary line for moving object by generating seeds with probability distribution function based on Watershed algorithm, and by extracting boundary line for moving objects through extending seeds, and then by using moving vectors. We processed tracking algorithm for moving object by using a part of boundary lines as features. We set up a part of every-direction boundary line for moving object as the initial feature vectors for moving objects. Then, we tracked moving object within current frames by using feature vector for the previous frames. As the result of the simulation for tracking moving object on the real images, we found that tracking processing of the proposed algorithm was simple due to tracking boundary line only for moving object as a feature, in contrast to the traditional tracking algorithm for active contour line that have varying processing cost with the length of boundary line. The operations was reduced about 39% as contrasted with the full search BMA. Tracking error was less than 4 pixel when the feature vector was $(15\times{5)}$ through the information of every-direction boundary line. The proposed algorithm just needed 200 times of search operation.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.648-651
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• 2003

In this paper, we propose the recognition system of a license plate using SOM algorithm. The recognition of license plate was investigated by means of the SOM algorithm. The morphological information of horizontal and vertical edges was used to extract a plate region from a car image. In addition, the 4-direction contour tracking algorithm was applied to extract the specific area, which includes characters from an extracted plate area. Therefore, we proposed how to extract license plate region using morphological information and how to recognize the character string using SOM algorithm. In this paper, 50 car images were tested. The extraction rate obtained by the proposed extraction method showed better results than that from the color information of RGB and HSI, respectively. And the license plate recognition using SOM algorithm was very efficient.