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Image Segmentation Using KFTBES

  • Yi-Fan Li
  • Wei Cui
  • Jeng-Shyang Pan
  • Jun-Bao Li
  • Qiang Su
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 387)

Abstract

We present a supervised algorithm to improve the image segmentation algorithm based on texture and boundary encoding. Our method is due to the analysis of the implementation and result of the TBES algorithms, and we increase the adaptability of the TBES algorithms. Through constructing the train dataset with fine-class segmentation, our method adaptively distribute the optimum segmentation standard to each image using Kernel Fisher algorithms. We also compare our method to other similar popular algorithms and our method achieves the state-of-the-art results on Berkeley Segmentation Dataset.

Keywords

Image segmentation TBES algorithm Kernel Fisher 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Yi-Fan Li
    • 1
  • Wei Cui
    • 1
  • Jeng-Shyang Pan
    • 1
    • 2
  • Jun-Bao Li
    • 3
  • Qiang Su
    • 1
  1. 1.Innovative Information Industry Research Center, Shenzhen Graduate SchoolHarbin Institute of TechnologyShenzhenChina
  2. 2.College of Information Science and EngineeringFujian University of TechnologyFuzhouChina
  3. 3.Department of Automatic Test and ControlHarbin Institute of TechnologyHarbinChina

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