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Segmentation of small objects in color images

Abstract

A method for effective segmentation of small objects in color images is presented. It can be used jointly with region growing algorithms. Segmentation of small objects in color images is a difficult problem because their boundaries are close to each other. The proposed algorithm accurately determines the location of the boundary points of closely located small objects and finds the skeletons (seed regions) of those objects. The method makes use of conditions obtained by analyzing the change of color characteristics of the edge pixels along the direction that is orthogonal to the boundaries of adjacent objects. These conditions are generalized for the case of the well-known class of color images having misregistration artifacts. If high-quality seed regions are available, the final segmentation can be performed using one of the region growing methods. The segmentation algorithm based on the proposed method was tested using a large number of color images, and it proved to be very efficient.

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Correspondence to V. L. Arlazarov.

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Original Russian Text © V.L. Arlazarov, M.D. Kazanov, 2008, published in Programmirovanie, 2008, Vol. 34, No. 3.

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Arlazarov, V.L., Kazanov, M.D. Segmentation of small objects in color images. Program Comput Soft 34, 173–182 (2008). https://doi.org/10.1134/S0361768808030055

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  • DOI: https://doi.org/10.1134/S0361768808030055

Keywords

  • Color Image
  • Small Object
  • Seed Region
  • Optical Character Recognition
  • Gradient Image