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Machine Vision and Applications

, Volume 29, Issue 4, pp 677–687 | Cite as

An experimental comparison of superpixels detection methods for contour detection

  • Xuan-Yin Wang
  • Chang-Wei Wu
  • Ke Xiang
  • Sen-Wei Xiang
  • Wen Chen
Original Paper
  • 214 Downloads

Abstract

Recently, many superpixels detection methods have been proposed and used in various applications. We are interested in which method is more suitable for the application of contour detection. In this paper, superpixels are evaluated on BSDS500 dataset in two different aspects. On the one hand, contours are directly provided by the boundaries of superpixels and experiments show that better results could be achieved by the superpixels with irregular shapes than those with regular shapes and similar sizes. On the other hand, contours are further detected from those candidate positions which are confirmed by the boundaries of superpixels through the operation of dilation. In this situation, experiments show that competitive results could also be achieved by some superpixels with regular shapes and similar sizes. Besides, we propose a superpixels detection method called watershed-based graph (WG), by which superpixels with irregular shapes could be produced. Firstly, a graph is constructed from an over-segmented map which is achieved through a watershed algorithm. Then, to get the desired superpixels, the graph is segmented by merging neighbor segments in an order of decreasing similarity. Experiments show that higher efficiency could be achieved by WG with a moderate worse contour quality than its original graph-based method.

Keywords

Superpixels Region merging Contour detection Image segmentation 

Notes

Acknowledgements

This work is supported by the Science Fund for Creative Research Groups of National Natural Science Foundation of China (Grant No. 51521064) and by the innovation fund of Shanghai Academy of Spaceflight Technology (Grant No. SAST2015086).

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.State Key Laboratory of Fluid Power and Mechatronic Systems, Mechanical EngineeringZhejiang UniversityHangzhouChina
  2. 2.Shanghai Key Laboratory of Aerospace Intelligent Control TechnologyShanghai Institute of Spaceflight Control TechnologyShanghaiChina

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