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A Hierarchical Finite-State Model for Texture Segmentation

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3 Author(s)
Scarpa, G. ; ARIANA Res. Group, France ; Haindl, M. ; Zerubia, J.

A novel model for unsupervised segmentation of texture images is presented. The image to be segmented is first discretized and then a hierarchical finite-state region-based model is automatically coupled with the data by means of a sequential optimization scheme, namely the texture fragmentation and reconstruction (TFR) algorithm. Both intra- and inter-texture interactions are modeled, by means of an underlying hierarchical finite-state model, and eventually the segmentation task is addressed in a completely unsupervised manner. The output is then a nested segmentation, so that the user may decide the scale at which the segmentation has to be provided. TFR is composed of two steps: the former focuses on the estimation of the states at the finest level of the hierarchy, and is associated with an image fragmentation, or over-segmentation; the latter deals with the reconstruction of the hierarchy representing the textural interaction at different scales.

Published in:

Acoustics, Speech and Signal Processing, 2007. ICASSP 2007. IEEE International Conference on  (Volume:1 )

Date of Conference:

15-20 April 2007