Abstract
This paper proposes a new color representation. This representation belongs to the penta-valued category and it has three chromatic components (red, blue and green) and two achromatic components (black and white). The proposed penta-valued representation is obtained by constructing a fuzzy partition in the RGB color space. In the structure of the penta-valued representation, it is defined the well known negation operator and supplementary, two new unary operators: the dual and the complement. Also, using the Bhattacharyya formula, it is defined a new inter-color similarity. Next, the obtained inter-color similarity is used in the framework of k-means clustering algorithm. On this way, it results a new color image clustering method. Some examples are presented in order to prove the effectiveness of the proposed multi-valued color descriptor.
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Patrascu, V. (2014). A Novel Penta-Valued Descriptor for Color Clustering. In: Elmoataz, A., Lezoray, O., Nouboud, F., Mammass, D. (eds) Image and Signal Processing. ICISP 2014. Lecture Notes in Computer Science, vol 8509. Springer, Cham. https://doi.org/10.1007/978-3-319-07998-1_20
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DOI: https://doi.org/10.1007/978-3-319-07998-1_20
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