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Object extraction in gray-scale images by optimizing roughness measure of a fuzzy set

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2005) 3776 LNCS 744-749
DOI: 10.1007/11590316_120
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Abstract

Object extraction from gray-tone images involve handling of inherent uncertainties in an image. Traditionally fuzzy set theoretic techniques are used for this purpose. However, roughness and limited discernibility of objects is another important aspect of image uncertainty. In this article we propose an algorithm for selection of intensity threshold for object extraction by optimizing a roughness measure of the fuzzy set corresponding to the image object. The rough-fuzzy algorithm is tested on some benchmark images. © Springer-Verlag Berlin Heidelberg 2005.

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Janardhan Rao, D. V., Banerjee, M., & Mitra, P. (2005). Object extraction in gray-scale images by optimizing roughness measure of a fuzzy set. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3776 LNCS, pp. 744–749). https://doi.org/10.1007/11590316_120

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