Abstract
This paper proposes unsupervised perceptual segmentation of natural color images using a fuzzy-based hierarchical algorithm. L ⋆ a ⋆ b ⋆ color space is used to represent color features and statistical geometrical features are adopted as texture features. A fuzzy-based homogeneity measure makes a fusion of color features and texture features. Proposed hierarchical segmentation method is performed in four stages: simple splitting, local merging, global merging and boundary refinement. Experiments on segmentation of natural color images are presented to verify the effectiveness of the proposed method in obtaining perceptual segmentation.
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Maeda, J., Kawano, A., Saga, S., Suzuki, Y. (2007). Unsupervised Perceptual Segmentation of Natural Color Images Using Fuzzy-Based Hierarchical Algorithm. In: Ersbøll, B.K., Pedersen, K.S. (eds) Image Analysis. SCIA 2007. Lecture Notes in Computer Science, vol 4522. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73040-8_47
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DOI: https://doi.org/10.1007/978-3-540-73040-8_47
Publisher Name: Springer, Berlin, Heidelberg
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