한국지능시스템학회:학술대회논문집 (Proceedings of the Korean Institute of Intelligent Systems Conference)
- 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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- Pages.476-479
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- 2003
A Possibilistic C-Means Approach to the Hough Transform for Line Detection
- Frank Chung-HoonRhee (Computation Vision and Fuzzy Systems Laboratory, Department of Electronic Engineering, Hanyang University) ;
- Shim, Eun-A (Computation Vision and Fuzzy Systems Laboratory Department of Electronic Engineering)
- 발행 : 2003.09.01
초록
The Rough transform (HT) is often used for extracting global features in binary images, for example curve and line segments, from local features such as single pixels. The HT is useful due to its insensitivity to missing edge points and occlusions, and robustness in noisy images. However, it possesses some disadvantages, such as time and memory consumption due to the number of input data and the selection of an optimal and efficient resolution of the accumulator space can be difficult. Another problem of the HT is in the difficulty of peak detection due to the discrete nature of the image space and the round off in estimation. In order to resolve the problem mentioned above, a possibilistic C-means approach to clustering [1] is used to cluster neighboring peaks. Several experimental results are given.
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