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• W2970804586 abstract "Most superpixel algorithms compute a trade-off between spatial and color features at the pixel level. Hence, they may need fine parameter tuning to balance the two measures, and highly fail to group pixels with similar local texture properties. In this paper, we address these issues with a new Texture-Aware SuperPixel (TASP) method. To accurately segment textured and smooth areas, TASP automatically adjusts its spatial constraint according to the local feature variance. Then, to ensure texture homogeneity within superpixels, a new pixel to super-pixel patch-based distance is proposed. TASP outperforms the segmentation accuracy of the state-of-the-art methods on texture and also natural color image datasets." @default.
• W2970804586 created "2019-09-05" @default.
• W2970804586 creator A5041896919 @default.
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• W2970804586 date "2019-09-01" @default.
• W2970804586 modified "2023-09-25" @default.
• W2970804586 title "Texture-Aware Superpixel Segmentation" @default.
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• W2970804586 doi "https://doi.org/10.1109/icip.2019.8803085" @default.
• W2970804586 hasPublicationYear "2019" @default.
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