Fuzzy Superpixel-based Image Segmentation

•A measure of connectivity between fuzzy superpixels and refined superpixels by their spatial intersection is proposed.•A novel fuzzy superpixel aggregation algorithm is developed.•A mean-shift-based merging approach with the spatial bandwidth adjustment strategy is proposed. This article presents a...

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Vydané v:Pattern recognition Ročník 134; s. 109045
Hlavní autori: Ng, Tsz Ching, Choy, Siu Kai, Lam, Shu Yan, Yu, Kwok Wai
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier Ltd 01.02.2023
Predmet:
Fuzzy algorithm
Graph theory
Mean-shift
Segmentation
Superpixel
Superpixel
Graph theory
Fuzzy algorithm
Segmentation
Mean-shift
ISSN:0031-3203, 1873-5142
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Popis
Shrnutí:•A measure of connectivity between fuzzy superpixels and refined superpixels by their spatial intersection is proposed.•A novel fuzzy superpixel aggregation algorithm is developed.•A mean-shift-based merging approach with the spatial bandwidth adjustment strategy is proposed. This article presents a multi-phase image segmentation methodology based on fuzzy superpixel decomposition, aggregation and merging. First, a collection of layers of dense fuzzy superpixels is generated by the variational fuzzy decomposition algorithm. Then a layer of refined superpixels is extracted by aggregating various layers of dense fuzzy superpixels using the hierarchical normalized cuts. Finally, the refined superpixels are projected into the low dimensional feature spaces by the multidimensional scaling and the segmentation result is obtained via the mean-shift-based merging approach with the spatial bandwidth adjustment strategy. Our algorithm utilizes the superimposition of fuzzy superpixels to impose more accurate spatial constraints on the final segmentation through the fuzzy superpixel aggregation. The fuzziness of superpixels also provides spatial features to measure affinities between fuzzy superpixels and refined superpixels, and guide the merging process. Comparative experiments with the existing approaches reveal a superior performance of the proposed method.
ISSN:0031-3203
1873-5142
DOI:10.1016/j.patcog.2022.109045