Homogeneous Superpixels from Markov Random Walks

  title={Homogeneous Superpixels from Markov Random Walks},
  author={Frank Perbet and Bj{\"o}rn Stenger and Atsuto Maki},
  journal={IEICE Transactions},
This paper presents a novel algorithm to generate homogeneous superpixels from Markov random walks. We exploit Markov clustering (MCL) as the methodology, a generic graph clustering method based on stochastic flow circulation. In particular, we introduce a graph pruning strategy called compact pruning in order to capture intrinsic local image structure. The resulting superpixels are homogeneous, i.e. uniform in size and compact in shape. The original MCL algorithm does not scale well to a graph… CONTINUE READING


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