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A fast scheme for optimal thresholding using genetic algorithms
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DOI：10.1016/S0165-1684(98)00167-4.png)
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Traditional optimal thresholding methods are very popular and efficient in the case of bi-level thresholding. But they are very computationally expensive when extended to multilevel thresholding since they exhaustively search the optimal thresholds to optimize the objective functions. In this paper, a fast scheme using genetic algorithms is proposed to render these optimal thresholding techniques more practical. The experimental results show that the proposed scheme can make the optimal thresholding methods applicable in the case of multilevel thresholding and the performances are better than those of some property-based multilevel thresholding methods. (C) 1999 Elsevier Science B.V. All rights reserved.
Keyword:
genetic algorithms
image segmentation
multilevel thresholding
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