ISSN 0253-2778

CN 34-1054/N

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An unsupervised boundary detection algorithm based on orientation contrast model

  • 1.

    College of Mathematics and Information Science, Key Lab. of Machine Learning and Computational Intelligence, Hebei University, Baoding 071102, China

  • 2.

    Comprehensive Experimental Center of Hebei University, Baoding 071102, China

Cite this: JUSTC, 2017, 47(1): 26-31
https://doi.org/10.3969/j.issn.0253-2778.2017.01.004
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  • Received Date: February 29, 2016
  • Revised Date: September 16, 2016
  • Published Date: January 30, 2017
    Abstract
  • For large image sets on the Web, due to the absense of a ground truth boundary or the high cost of getting one, an unsupervised boundary detection algorithm based on orientation contrast model was proposed. The model is especially suited for detecting object boundaries surrounded by natural textures. In the Rug image database, the algorithm outperforms the state-of-the-art unsupervised boundary detection algorithm, which verifies the validity of the model.
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