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.
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Rao, D.V.J., Banerjee, M., Mitra, P. (2005). Object Extraction in Gray-Scale Images by Optimizing Roughness Measure of a Fuzzy Set. In: Pal, S.K., Bandyopadhyay, S., Biswas, S. (eds) Pattern Recognition and Machine Intelligence. PReMI 2005. Lecture Notes in Computer Science, vol 3776. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11590316_120
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DOI: https://doi.org/10.1007/11590316_120
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30506-4
Online ISBN: 978-3-540-32420-1
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