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A superpixel segmentation algorithm based on differential evolution
Gong Y.-J.2; Zhou Y.2; Zhang X.1
Conference NameIEEE International Conference on Multimedia & Expo (ICME)
Source PublicationProceedings - IEEE International Conference on Multimedia and Expo
Conference DateJUL 11-15, 2016
Conference PlaceSeattle, WA

This paper deals with the superpixel segmentation problem using a powerful global optimization technique: Differential Evolution. The algorithm mimics the process of nature evolution to realize efficient optimization, and it poses no restrictions on the form of objective functions. This way, we develop a novel and comprehensive objective function considering both local and global costs in the segmentation, including within-superpixel error, boundary gradient, a regularization term. The proposed method can produce superpixels in a computational time linear to the image size. Experimental results validate the competitive performance of our algorithm in terms of boundary adherence and segmentation capability.

KeywordClustering Differential Evolution Evolutionary Computation Segmentation Superpixel
URLView the original
Indexed BySCI
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Software Engineering ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS IDWOS:000389574300133
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Document TypeConference paper
CollectionFaculty of Science and Technology
Affiliation1.South China University of Technology
2.Universidade de Macau
3.Sun Yat-Sen University
Recommended Citation
GB/T 7714
Gong Y.-J.,Zhou Y.,Zhang X.. A superpixel segmentation algorithm based on differential evolution[C],2016.
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