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- W2948820902 abstract "Superpixel segmentation can benefit from the use of an appropriate method to measure edge strength. In this paper, we present such a method based on the first derivative of anisotropic Gaussian kernels. The kernels can capture the position, direction, prominence, and scale of the edge to be detected. We incorporate the anisotropic edge strength into the distance measure between neighboring superpixels, thereby improving the performance of an existing graph-based superpixel segmentation method. Experimental results validate the superiority of our method in generating superpixels over the competing methods. It is also illustrated that the proposed superpixel segmentation method can facilitate subsequent saliency detection." @default.
- W2948820902 created "2019-06-14" @default.
- W2948820902 creator A5014127586 @default.
- W2948820902 creator A5032988165 @default.
- W2948820902 date "2019-06-05" @default.
- W2948820902 modified "2023-09-27" @default.
- W2948820902 title "Superpixel Segmentation Based on Anisotropic Edge Strength" @default.
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- W2948820902 doi "https://doi.org/10.3390/jimaging5060057" @default.
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