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Titlebook: Edge Detection Methods Based on Generalized Type-2 Fuzzy Logic; Claudia I. Gonzalez,Patricia Melin,Oscar Castillo Book 2017 The Author(s)

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ved by the T1 and IT2 fuzzy edge detection methods..Additionally, in this section we also present a comparative analysis with the recognition rates achieved by the GT2 against the results obtained by T1 and T2 fuzzy edge detectors; when these are applied on a face recognition system.
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Edge Detection Methods Based on Generalized Type-2 Fuzzy Logic Systems,orphological gradient. The second is the edge detection method based on GT2 FSs and the Sobel operator. The third is the generalized type-2 fuzzy edge detection method applied on color images and finally, the edge detection method using GT2 fuzzy images.
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Experimentation and Results Discussion,ved by the T1 and IT2 fuzzy edge detection methods..Additionally, in this section we also present a comparative analysis with the recognition rates achieved by the GT2 against the results obtained by T1 and T2 fuzzy edge detectors; when these are applied on a face recognition system.
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https://doi.org/10.1057/9780230524101alized type-2 is needed in real-world devices and applications, in particular in the image processing area that is the case study in this book, because the devices that capture digital images are always exposed to external interference adding high noise levels or uncertainty to the images.
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Book 2017ormat..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 u
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Edge Detection Methods Based on Generalized Type-2 Fuzzy Logic
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2191-530X r 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 u978-3-319-53993-5978-3-319-53994-2Series ISSN 2191-530X Series E-ISSN 2191-5318
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