Fast Superpixel Segmentation via Boundary Sampling and Interpolation

Li XU  Bing LUO  Mingming KONG  Bo LI  Zheng PEI  

IEICE TRANSACTIONS on Information and Systems   Vol.E102-D   No.4   pp.871-874
Publication Date: 2019/04/01
Publicized: 2019/01/22
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2018EDL8168
Type of Manuscript: LETTER
Category: Image Recognition, Computer Vision
superpixel,  acceleration,  sampling,  interpolation,  

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This letter proposes a fast superpixel segmentation method based on boundary sampling and interpolation. The basic idea is as follow: instead of labeling local region pixels, we estimate superpixel boundary by interpolating candidate boundary pixel from a down-sampling image segmentation. On the one hand, there exists high spatial redundancy within each local region, which could be discarded. On the other hand, we estimate the labels of candidate boundary pixels via sampling superpixel boundary within corresponding neighbour. Benefiting from the reduction of candidate pixel distance calculation, the proposed method significantly accelerates superpixel segmentation. Experiments on BSD500 benchmark demonstrate that our method needs half the time compared with the state-of-the-arts while almost no accuracy reduction.