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Edge Detection Methods Based on Generalized Type-2 Fuzzy Logic (Paperback, 1st ed. 2017)
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Edge Detection Methods Based on Generalized Type-2 Fuzzy Logic (Paperback, 1st ed. 2017)
Series: SpringerBriefs in Computational Intelligence
Expected to ship within 10 - 15 working days
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In this book four new methods are proposed. In the first method the
generalized type-2 fuzzy logic is combined with the morphological
gra-dient technique. The second method combines the general type-2
fuzzy systems (GT2 FSs) and the Sobel operator; in the third
approach the me-thodology based on Sobel operator and GT2 FSs is
improved to be applied on color images. In the fourth approach, we
proposed a novel edge detec-tion method where, a digital image is
converted a generalized type-2 fuzzy image. In this book it is also
included a comparative study of type-1, inter-val type-2 and
generalized type-2 fuzzy systems as tools to enhance edge detection
in digital images when used in conjunction with the morphologi-cal
gradient and the Sobel operator. The proposed generalized type-2
fuzzy edge detection methods were tested with benchmark images and
synthetic images, in a grayscale and color format. Another
contribution in this book is that the generalized type-2 fuzzy edge
detector method is applied in the preprocessing phase of a face
rec-ognition system; where the recognition system is based on a
monolithic neural network. The aim of this part of the book is to
show the advantage of using a generalized type-2 fuzzy edge
detector in pattern recognition applications. The main goal of
using generalized type-2 fuzzy logic in edge detec-tion
applications is to provide them with the ability to handle
uncertainty in processing real world images; otherwise, to
demonstrate that a GT2 FS has a better performance than the edge
detection methods based on type-1 and type-2 fuzzy logic systems.
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