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Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

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Segmentation of Gabor-filtered textures using deterministic relaxation.

P P Raghu¹, B Yegnanarayana

¹Indian Inst. of Technol., Madras.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society

|January 1, 1996

Summary

This summary is machine-generated.

This study introduces a supervised texture segmentation method using Gabor filters and a Hopfield network. The approach achieves optimal image segmentation by modeling texture features and maximizing a posteriori probability.

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Area of Science:

Computer Vision
Image Processing
Machine Learning

Background:

Texture segmentation is crucial for image analysis.
Existing methods often lack robustness in complex textured regions.
Supervised approaches require effective feature extraction and modeling.

Purpose of the Study:

To propose a novel supervised texture segmentation scheme.
To leverage Gabor filters for robust texture feature extraction.
To develop an efficient segmentation model using Markov Random Fields and Hopfield networks.

Main Methods:

Image filtering using a Gabor filter bank with varying frequencies, resolutions, and orientations.
Feature formation modeling texture features as Gaussian distributions.
Image partition using a noncausal Markov Random Field (MRF).
Competition process for pixel label assignment.
Hopfield network implementation for energy minimization and Maximum a Posteriori (MAP) estimation.

Main Results:

The proposed scheme effectively segments textured images.
Demonstrated performance on diverse image datasets, including remote sensing imagery.
Achieved optimal segmentation through deterministic relaxation to the minimum energy state.

Conclusions:

The developed supervised texture segmentation scheme provides an effective solution.
The integration of Gabor filters, MRF, and Hopfield networks offers a powerful approach for image segmentation.
The method shows promise for applications in remote sensing and other image analysis domains.