Abstract
This paper focuses on application of fuzzy sets of type 2 (FS2) in color images segmentation. The proposed approach is based on FS2 entropy application and region merging. Both local and global information of the image are employed and FS2 makes it possible to take into account the total uncertainty inherent to the segmentation operation. Fuzzy entropy is utilized as a tool to perform histogram analysis to find all major homogeneous regions at the first stage. Then a basic and fast region merging process, based on color similarity and reduction of small clusters, is carried out to avoid oversegmentation. The experimental results demonstrate that this method is suitable to find homogeneous regions for natural images, even for noisy images.
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Tehami, S., Bigand, A., Colot, O. (2007). Color Image Segmentation Based on Type-2 Fuzzy Sets and Region Merging. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2007. Lecture Notes in Computer Science, vol 4678. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74607-2_86
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DOI: https://doi.org/10.1007/978-3-540-74607-2_86
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