Topographic Independent Component Analysis Based on Fractal and Morphology Applied to Texture Segmentation

Authors:
Klaus Fabian Côco;Evandro Ottoni Salles;Mário Sarcinelli-Filho
Affiliations:
Graduate Program on Electrical Engineering, Federal University of Espirito Santo, Vitoria, Brazil 514 29075-910;Graduate Program on Electrical Engineering, Federal University of Espirito Santo, Vitoria, Brazil 514 29075-910;Graduate Program on Electrical Engineering, Federal University of Espirito Santo, Vitoria, Brazil 514 29075-910
Venue:
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
Year:
2009

Citing 5
Cited 0

Fractal Geometry in Digital Imaging

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Independent Component Analysis of Textures

ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Topographic Independent Component Analysis

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Emergence of Phase- and Shift-Invariant Features by Decomposition of Natural Images into Independent Feature Subspaces

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Morphology-based multifractal estimation for texture segmentation

IEEE Transactions on Image Processing

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Abstract

The topographic independent component analysis (TICA) is a technique for texture segmentation in which the image base is obtained from the mixture matrix of the model through a bank of statistical filters. The use of energy as the topographic criterion in connection with the TICA filter bank has been explored in the literature, with good results. In such context, this paper proposes the use of energy plus a morphologic fractal descriptor as a new topographic criterion to be used in connection with the TICA filter bank. The new approach, called TICA fractal multi-scale (TICAFS) approach, results in a meaningful reduction of the segmentation error and/or in a meaningful reduction in the number of filters, when compared to the TICA energy (TICAE) approach.