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Attribute Operators for Color Images: Image Segmentation Improved by the Use of Unsupervised Segmentation Evaluation Methods

  • Sérgio Sousa Filho
  • Franklin César Flores
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10225)

Abstract

Attribute openings and thinnings are morphological connected operators that remove structures from images according to a given criterion. These operators were successfully extended from binary to grayscale images, but such extension to color images is not straightforward. This paper proposes color attribute operators by a combination of color gradients and thresholding decomposition. In this approach, not only structural criteria may be applied, but also criteria based on color features and statistics. This work proposes, in a segmentation framework, two criteria based on unsupervised segmentation evaluation for improvement of color segmentation. Segmentation using our operators performed better than two state-of-the-art methods in 80% of the experiments done using 300 images.

Keywords

Attribute filter Image segmentation Thresholding decomposition Color processing 

Notes

Acknowledgment

First author would like to thank Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Brazil, for the master scholarship. Second author would like to thank Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Brazil, for the post-doctoral scholarship.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Department of InformaticsState University of MaringáMaringáBrazil

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