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An Enhanced Louvain Based Image Segmentation Approach Using Color Properties and Histogram of Oriented Gradients

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Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1182))

Abstract

Segmentation techniques based on community detection algorithms generally have an over-segmentation problem. This paper then propose a new algorithm to agglomerate near homogeneous regions based on texture and color features. More specifically, our strategy relies on the use of a community detection on graphs algorithm (used as a clustering approach) where the over-segmentation problem is managed by merging similar regions in which the similarity is computed with Histogram of Oriented Gradients (named as HOG) and Mean and Standard deviation of color properties as features. In order to assess the performances of our proposed algorithm, we used three public datasets (Berkeley Segmentation Dataset (BSDS300 and BSDS500) and the Microsoft Research Cambridge Object Recognition Image Database (MSRC)). Our experiments show that the proposed method produces sizable segmentation and outperforms almost all the other methods from the literature, in terms of accuracy and comparative metrics scores.

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Authors and Affiliations

  1. L3i Laboratory, Faculty of Science and Technology, University of La Rochelle, Avenue Michel Crepeau, 17042, La Rochelle Cedex 1, France

    Thanh-Khoa Nguyen, Jean-Loup Guillaume & Mickael Coustaty

  2. Ca Mau Community College, Ca Mau, Vietnam

    Thanh-Khoa Nguyen

Authors
  1. Thanh-Khoa Nguyen
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  2. Jean-Loup Guillaume
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  3. Mickael Coustaty
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Corresponding author

Correspondence to Thanh-Khoa Nguyen .

Editor information

Editors and Affiliations

  1. University of Lisbon, Lisbon, Portugal

    Ana Paula Cláudio

  2. University of Rennes 1, Rennes, France

    Kadi Bouatouch

  3. University of Genoa, Genoa, Italy

    Manuela Chessa

  4. Mines ParisTech, Paris, France

    Alexis Paljic

  5. Linnaeus University, Växjö, Sweden

    Andreas Kerren

  6. French Civil Aviation University (ENAC), Toulouse, France

    Christophe Hurter

  7. University Jean Monnet, Saint-Etienne, France

    Alain Tremeau

  8. University of Catania, Catania, Italy

    Giovanni Maria Farinella

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Nguyen, TK., Guillaume, JL., Coustaty, M. (2020). An Enhanced Louvain Based Image Segmentation Approach Using Color Properties and Histogram of Oriented Gradients. In: Cláudio, A., et al. Computer Vision, Imaging and Computer Graphics Theory and Applications. VISIGRAPP 2019. Communications in Computer and Information Science, vol 1182. Springer, Cham. https://doi.org/10.1007/978-3-030-41590-7_23

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  • DOI: https://doi.org/10.1007/978-3-030-41590-7_23

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  • Online ISBN: 978-3-030-41590-7

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