Abstract
This paper presents a computational model that segments images based on the textural properties of object surfaces. The proposed Coupled-Membrane model applies the weak membrane approach to an image WI(σ,θ, x, y), derived from the power responses of a family of selfsimilar quadrature Gabor wavelets. While segmentation breaks are allowed in x and y only, coupling is introduced to in all 4 dimensions. The resulting spatial and spectral diffusion prevents minor variations in local textures from producing segmentation boundaries. Experiments showed that the model is adequate in segmenting a class of synthetic and natural texture images.
This research is supported in part by Harvard-MIT Division of Health Sciences & Technology and Harvard's Division of Applied Sciences' fellowship to T.S. Lee, Army Research Office grant DAAL03-86-0171 to D. Mumford, and NSF grant IRI-9003306 to A. Yuille. Interesting discussion and technical help from John Daugman, Mark Nitzberg, Peter Hallinan, Peter Belhumeur, Michael Weisman, and Petros Maragos are greatly appreciated.
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© 1992 Springer-Verlag Berlin Heidelberg
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Lee, T.S., Mumford, D., Yuille, A. (1992). Texture segmentation by minimizing vector-valued energy functionals: The Coupled-Membrane model. In: Sandini, G. (eds) Computer Vision — ECCV'92. ECCV 1992. Lecture Notes in Computer Science, vol 588. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-55426-2_19
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DOI: https://doi.org/10.1007/3-540-55426-2_19
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