Abstract
The paper consists of three parts. In the first part of the paper, a self-supervised learning algorithm with the concept of guard zones around the class representative vectors has been presented for vowel sound recognition. In the second part, an algorithm consisting of histogram equalisation technique followed by a further enhancement using fuzzy S and π membership functions is described for detecting the small variation in grey levels and identifying the different regional contours of x-ray images. Finally, a quantitative measure of image-quality is provided by the terms “index of fuzziness”, “entropy” and “π-ness” of a fuzzy set.
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© 1982 D. Reidel Publishing Company
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Pal, S.K. (1982). Fuzzy Set Theoretic Approach: A Tool for Speech and Image Recognition. In: Kittler, J., Fu, K.S., Pau, LF. (eds) Pattern Recognition Theory and Applications. NATO Advanced Study Institutes Series, vol 81. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-7772-3_9
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DOI: https://doi.org/10.1007/978-94-009-7772-3_9
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-009-7774-7
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