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International Symposium on Mathematical Morphology and Its Applications to Signal and Image Processing

ISMM 2017: Mathematical Morphology and Its Applications to Signal and Image Processing pp 249–260Cite as

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

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Part of the book series: Lecture Notes in Computer Science ((LNIP,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.

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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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Authors and Affiliations

  1. Department of Informatics, State University of Maringá, Maringá, Paraná, Brazil

    Sérgio Sousa Filho & Franklin César Flores

Authors
  1. Sérgio Sousa Filho
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  2. Franklin César Flores
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Correspondence to Sérgio Sousa Filho .

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Editors and Affiliations

  1. MINES ParisTech, PSL-Research University, Fontainebleau, France

    Jesús Angulo

  2. MINES ParisTech, PSL-Research University , Fontainebleau, France

    Santiago Velasco-Forero

  3. MINES ParisTech, PSL-Research University, Fontainebleau, France

    Fernand Meyer

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Sousa Filho, S., Flores, F.C. (2017). Attribute Operators for Color Images: Image Segmentation Improved by the Use of Unsupervised Segmentation Evaluation Methods. In: Angulo, J., Velasco-Forero, S., Meyer, F. (eds) Mathematical Morphology and Its Applications to Signal and Image Processing. ISMM 2017. Lecture Notes in Computer Science(), vol 10225. Springer, Cham. https://doi.org/10.1007/978-3-319-57240-6_20

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  • DOI: https://doi.org/10.1007/978-3-319-57240-6_20

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  • Print ISBN: 978-3-319-57239-0

  • Online ISBN: 978-3-319-57240-6

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