Publication details

Hierarchical Finite-State Modeling for Texture Segmentation with Application to Forest Classification

Research Report

Scarpa G., Haindl Michal, Zerubia J.

publisher: Institut National de Recherche en Informatique et en Automatique, (Sophia Antipolis 2006)

edition: Research Report 6066

research: CEZ:AV0Z10750506

project(s): 507752,

keywords: Texture segmentation, classification, co-occurrence matrix, structural models, Markov chain, texture synthesis, forest classification

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abstract (eng):

In this research report we present a new model for texture representation which is particularly well suited for image analysis and segmentation. Any image 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. The TFR algorithm allows to model both intra- and inter-texture interactions, and eventually addresses the segmentation task in a completely unsupervised manner. Moreover, it provides a hierarchical output, as the user may decide the scale at which the segmentation has to be given. Tests were carried out on both natural texture mosaics provided by the Prague Texture Segmentation Datagenerator Benchmark and remote-sensing data of forest areas provided by the French National Forest Inventory (IFN).

abstract (cze):

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