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Yet Another Survey on Image Segmentation: Region and Boundary Information Integration

Part of the Lecture Notes in Computer Science book series (LNCS,volume 2352)

Abstract

Image segmentation has been, and still is, a relevant research area in Computer Vision, and hundreds of segmentation algorithms have been proposed in the last 30 years. However, it is well known that elemental segmentation techniques based on boundary or region information often fail to produce accurate segmentation results. Hence, in the last few years, there has been a tendency towards algorithms which take advantage of the complementary nature of such information. This paper reviews different segmentation proposals which integrate edge and region information and highlights 7 different strategies and methods to fuse such information. In contrast with other surveys which only describe and compare qualitatively different approaches, this survey deals with a real quantitative comparison. In this sense, key methods have been programmed and their accuracy analyzed and compared using synthetic and real images. A discussion justified with experimental results is given and the code is available on Internet.

Keywords

  • grouping and segmentation
  • region based segmentation
  • boundary based segmentation
  • cooperative segmentation methods

This work was partially supported by the Departament d’Universitats, Recerca i Societat de la Informació de la Generalitat de Catalunya.

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© 2002 Springer-Verlag Berlin Heidelberg

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Freixenet, J., Muñoz, X., Raba, D., Martí, J., Cufí, X. (2002). Yet Another Survey on Image Segmentation: Region and Boundary Information Integration. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds) Computer Vision — ECCV 2002. ECCV 2002. Lecture Notes in Computer Science, vol 2352. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47977-5_27

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  • DOI: https://doi.org/10.1007/3-540-47977-5_27

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