An improved watershed image segmentation algorithm  combining with a new entropy evaluation criterion

Tingquan Deng; Yanchao Li

doi:10.1117/12.2014197

13 March 2013 An improved watershed image segmentation algorithm combining with a new entropy evaluation criterion

Tingquan Deng, Yanchao Li

Proceedings Volume 8784, Fifth International Conference on Machine Vision (ICMV 2012): Algorithms, Pattern Recognition, and Basic Technologies; 87841V (2013) https://doi.org/10.1117/12.2014197
Event: Fifth International Conference on Machine Vision (ICMV 12), 2012, Wuhan, China

Abstract

An improved watershed image segmentation algorithm is proposed to solve the problem of over-segmentation by classical watershed algorithm. The new algorithm combines region growing with classical watershed algorithm. The key to region growing lies in choosing a growing threshold to reach a desired result of image segmentation. An entropy evaluation criterion is constructed to determine the optimal threshold. Considering the entropy evaluation criterion as an objective function, the particle swarm optimization algorithm is employed to search global optimization of the objective function. Experimental results show that this new algorithm can solve the problem of over-segmentation effectively.

Citation Download Citation

Tingquan Deng and Yanchao Li "An improved watershed image segmentation algorithm combining with a new entropy evaluation criterion", Proc. SPIE 8784, Fifth International Conference on Machine Vision (ICMV 2012): Algorithms, Pattern Recognition, and Basic Technologies, 87841V (13 March 2013); https://doi.org/10.1117/12.2014197

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