Abstract
Texture and color are important cues in visual tasks such as image segmentation, classification and retrieval. In this work we propose an approach to image segmentation based on fuzzy feature distributions of color and texture information. Fuzzy C-Means clustering with spatial constraints is applied to the features extracted in the HSI color space. The effectiveness of the proposed approach is evaluated on a set of artificial and natural texture images.
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Górecki, P., Caponetti, L. (2007). Color Texture Segmentation with Local Fuzzy Patterns and Spatially Constrained Fuzzy C-Means. In: Masulli, F., Mitra, S., Pasi, G. (eds) Applications of Fuzzy Sets Theory. WILF 2007. Lecture Notes in Computer Science(), vol 4578. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73400-0_46
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DOI: https://doi.org/10.1007/978-3-540-73400-0_46
Publisher Name: Springer, Berlin, Heidelberg
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