Abstract
In this paper, we propose a new method of the shape detection by using a self-organizing method with input vector transformation. It is difficult to detect a shape from a noisy image by the conventional Hough Transform. The proposed method enables to detect the shape automatically. Two SOMs are used in the proposed method, the first SOM determines the number of typical shapes included in the image and the second SOM determines the parameters of the shapes. The performance of the proposed method is confirmed by detection of lines and circles from noisy images.
This work was achieved when the author was a Graduate course student of Kyushu Institute of Technology.
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References
P. V. C. Hough, “Method and Means for Recognizing Complex Patterns,” U. S. Patent, 3069 654, 1962.
T. Kohonen, “Self-organized formation of topologically correct feature maps,” Biol. Cybern., Vol.43, pp.59–69, 1982.
T.Kohonen, Self-organization and associative memory, Springer-Verlag, 1988.
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© 2001 Springer-Verlag London Limited
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Yamakawa, T., Horio, K., Izumi, S., Miki, T. (2001). A New Method of Hough Transform by Using SOM with Input Vector Transformation. In: Advances in Self-Organising Maps. Springer, London. https://doi.org/10.1007/978-1-4471-0715-6_24
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DOI: https://doi.org/10.1007/978-1-4471-0715-6_24
Publisher Name: Springer, London
Print ISBN: 978-1-85233-511-3
Online ISBN: 978-1-4471-0715-6
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