期刊
PATTERN ANALYSIS AND APPLICATIONS
卷 20, 期 1, 页码 1-20出版社
SPRINGER
DOI: 10.1007/s10044-015-0450-x
关键词
Firefly meta-heuristic; Tsallis entropy; Image segmentation; Optimization
资金
- CNPq
- CAPES
In this paper we show that the non-extensive Tsallis entropy, when used as kernel in the bio-inspired firefly algorithm for multi-thresholding in image segmentation, is more efficient than using the traditional cross-entropy presented in the literature. The firefly algorithm is a swarm-based meta-heuristic, inspired by fireflies-seeking behavior following their luminescence. We show that the use of more convex kernels, as those based on non-extensive entropy, is more effective at of significance level than the cross-entropy counterpart when applied in synthetic spaces for searching thresholds in global minimum.
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