Superpixel Segmentation Based on Anisotropic Edge Strength
Keyword(s):
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.
2013 ◽
Vol 860-863
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pp. 2783-2786
Keyword(s):
2019 ◽
Vol 9
(3)
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pp. 23-37
Keyword(s):
2019 ◽
Vol 13
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pp. 174830261984578
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2012 ◽
Vol 217-219
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pp. 1964-1967
2012 ◽
Vol 155-156
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pp. 861-866
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2013 ◽
Vol 2013
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pp. 1-7
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1988 ◽
Vol 02
(02)
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pp. 301-319
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2020 ◽
Vol XLIII-B2-2020
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pp. 1225-1232