A Robust Color Watershed Transformation and Image Segmentation Defined on RGB Spherical Coordinates

Abstract : The representation of the RGB color space points in spherical coordinates allows to retain the chromatic components of image pixel colors, pulling apart easily the intensity component. This representation allows the definition of a chromatic distance and a hybrid gradient with good properties of perceptual color constancy. In this chapter, the authors present a watershed based image segmentation method using this hybrid gradient. Oversegmentation is solved by applying a region merging strategy based on the chromatic distance defined on the spherical coordinate representation. The chapter shows the robustness and performance of the approach on well known test images and the Berkeley benchmarking image database and on images taken with a NAO robot.
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Chapitre d'ouvrage
J. Garcia-Rodriguez and M. A. Cazorla Quevedo. Robotic Vision: Technologies for Machine Learning and Vision Applications, IGI Global Publisher, pp.112-128, 2013, 〈10.4018/978-1-4666-2672-0.ch007〉
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https://hal.archives-ouvertes.fr/hal-01568546
Contributeur : Lab Lissi <>
Soumis le : mardi 25 juillet 2017 - 13:20:12
Dernière modification le : lundi 18 février 2019 - 17:24:59

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R. Moreno, M. Graña, K. Madani. A Robust Color Watershed Transformation and Image Segmentation Defined on RGB Spherical Coordinates. J. Garcia-Rodriguez and M. A. Cazorla Quevedo. Robotic Vision: Technologies for Machine Learning and Vision Applications, IGI Global Publisher, pp.112-128, 2013, 〈10.4018/978-1-4666-2672-0.ch007〉. 〈hal-01568546〉

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