Abstract
A general methodology is introduced for texture segmentation in binary, scalar, or multispectral images. Textural information is obtained from morphological operations of images. Starting from a fine partition of the image in regions, hierarchical segmentations are designed in a probabilistic framework by means of probabilistic distances conveying the textural information, and of random markers accounting for the morphological content of the regions and of their spatial arrangement.
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Jeulin, D. (2015). Probabilistic Hierarchical Morphological Segmentation of Textures. In: Benediktsson, J., Chanussot, J., Najman, L., Talbot, H. (eds) Mathematical Morphology and Its Applications to Signal and Image Processing. ISMM 2015. Lecture Notes in Computer Science(), vol 9082. Springer, Cham. https://doi.org/10.1007/978-3-319-18720-4_27
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DOI: https://doi.org/10.1007/978-3-319-18720-4_27
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-18719-8
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