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Morphological Texture Analysis Using Optimization of Structuring Elements

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Geometry, Morphology, and Computational Imaging

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2616))

Abstract

This paper proposes a method of texture analysis using morphological size distribution. Our framework is based on the concept that a texture is described by estimation of primitive, size distribution of grains derived from the primitive, and spatial distribution of the grains. We concentrate on estimation of primitive using an assumption on grain size distribution. We assume a model that grains are derived from one primitive, and a uniform size distribution since we consider target textures containing grains of various sizes. Thus the structuring element used for the measurement of size distribution is optimized to obtain the most uniform size density function. The optimized structuring element is an estimate of the primitive under the assumption. Simulated annealing algorithm is employed for the optimization.

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References

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© 2003 Springer-Verlag Berlin Heidelberg

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Asano, A., Miyagawa, M., Fujio, M. (2003). Morphological Texture Analysis Using Optimization of Structuring Elements. In: Asano, T., Klette, R., Ronse, C. (eds) Geometry, Morphology, and Computational Imaging. Lecture Notes in Computer Science, vol 2616. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36586-9_9

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  • DOI: https://doi.org/10.1007/3-540-36586-9_9

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-00916-0

  • Online ISBN: 978-3-540-36586-0

  • eBook Packages: Springer Book Archive

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