ARCHETYPAL ANALYSIS: AN ALTERNATIVE TO CLUSTERING FOR UNSUPERVISED TEXTURE SEGMENTATION

Ismael Cabero, Irene Epifanio

Abstract

Texture segmentation is one of the main tasks in image applications, specifically in remote sensing, where the objective is to segment high-resolution images of natural landscapes into different cover types. Often the focus is on the selection of discriminant textural features, and although these are really fundamental, there is another part of the process that is also influential, partitioning different homogeneous textures into groups. A methodology based on archetype analysis (AA) of the local textural measurements is proposed. AA seeks the purest textures in the image and it can find the borders between pure textures, as those regions composed of mixtures of several archetypes. The proposed procedure has been tested on a remote sensing image application with local granulometries, providing promising results.


Keywords
archetype; image segmentation; local granulometries; mathematical morphology; texture analysis

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DOI: 10.5566/ias.2052

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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Image Analysis & Stereology
EISSN 1854-5165 (Electronic version)
ISSN 1580-3139 (Printed version)