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A Modified Edge-Based Region Growing Segmentation of Geometric Objects

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Visual Informatics: Sustaining Research and Innovations (IVIC 2011)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 7066))

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Abstract

Region growing and edge detection are two popular and common techniques used for image segmentation. Region growing is preferred over edge detection methods because it is more robust against low contrast problems and effectively addresses the connectivity issues faced by edge detectors. Edge-based techniques, on the other hand, can significantly reduce useless information while preserving the important structural properties in an image. Recent studies have shown that combining region growing and edge methods for segmentation will produce much better results. This paper proposed using edge information to automatically select seed pixels and guide the process of region growing in segmenting geometric objects from an image. The geometric objects are songket motifs from songket patterns. Songket motifs are the main elements that decorate songket pattern. The beauty of songket lies in the elaborate design of the patterns and combination of motifs that are intricately woven on the cloth. After experimenting on thirty songket pattern images, the proposed method achieved promising extraction of the songket motifs.

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Author information

Authors and Affiliations

  1. Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, 40450, Shah Alam, Selangor, Malaysia

    Nursuriati Jamil, Hazwani Che Soh & Zainab Abu Bakar

  2. Faculty of Technology and Information Sciences, Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor, Malaysia

    Tengku Mohd Tengku Sembok

Authors
  1. Nursuriati Jamil
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  2. Hazwani Che Soh
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  3. Tengku Mohd Tengku Sembok
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  4. Zainab Abu Bakar
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Editor information

Editors and Affiliations

  1. Universiti Kebangsaan Malaysia, Bangi, Malaysia

    Halimah Badioze Zaman

  2. University of Cambridge, UK

    Peter Robinson

  3. Imperial College, London, UK

    Maria Petrou

  4. Newcastle University upon-Tyne, UK

    Patrick Olivier

  5. National Central University, Jhongli City, Taiwan

    Timothy K. Shih

  6. Digital Imaging Research Centre, Kingston University, London Kingston-Upon-Thames, KT1 2EE, UK

    Sergio Velastin

  7. Centre for Image Analysis, Uppsala University, Uppsala, Sweden

    Ingela Nyström

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© 2011 Springer-Verlag Berlin Heidelberg

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Jamil, N., Soh, H.C., Tengku Sembok, T.M., Bakar, Z.A. (2011). A Modified Edge-Based Region Growing Segmentation of Geometric Objects. In: Badioze Zaman, H., et al. Visual Informatics: Sustaining Research and Innovations. IVIC 2011. Lecture Notes in Computer Science, vol 7066. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25191-7_11

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  • DOI: https://doi.org/10.1007/978-3-642-25191-7_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25190-0

  • Online ISBN: 978-3-642-25191-7

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