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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Li Li Jian Yao Jinge Tu Xiaohu Lu Kai Li Yahui Liu |
| Copyright Year | 2015 |
| Description | Author affiliation: Sch. of Remote Sensing & Inf. Eng., Wuhan Univ., Wuhan, China (Li Li; Jian Yao; Jinge Tu; Xiaohu Lu; Kai Li; Yahui Liu) |
| Abstract | Superpixels are an oversegmentation of an image and popularly used as a preprocessing in many computer vision applications. Many state-of-the-art superpixel segmentation algorithms rely either on minimizing special energy functions or on clustering pixels in the effective distance space. While in this paper, we introduce a novel algorithm to produce superpixels based on the edge map by utilizing a split-andmerge strategy. Firstly, we obtain the initial superpixels with uniform size and shape. Secondly, in the splitting stage, we find all possible splitting contours for each superpixel by overlapping the boundaries of this superpixel with the edge map, and then choose the best one to split it which ensure the superpixels produced by this splitting are dissimilarity in color and similarity in size. Thirdly, in the merging stage, the Bhattacharyya distance between two color histograms in the RGB space for each pair of adjacent superpixels is computed to evaluate their color similarity for merging superpixels. At last, we iterate the split-and-merge steps until no superpixels have changed. Experimental results on the Berkeley Segmentation Dataset (BSD) show that the proposed algorithm can achieve a good performance compared with the state-of-the-art superpixel segmentation algorithms. |
| Starting Page | 970 |
| Ending Page | 975 |
| File Size | 4707036 |
| Page Count | 6 |
| File Format | |
| e-ISBN | 9781467391047 |
| DOI | 10.1109/ICInfA.2015.7279427 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-08-08 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Image segmentation Histograms Split-and-Merge Image color analysis Shape Edge Drawing Image edge detection Merging Clustering algorithms Image Segmentation Superpixels |
| Content Type | Text |
| Resource Type | Article |
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