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Edge Detection Methods Based on Generalized Type-2 Fuzzy Logic / by Claudia I. Gonzalez, Patricia Melin, Juan R. Castro, Oscar Castillo.

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Tipo de material: Texto

TextoSeries SpringerBriefs in Computational Intelligence | | SpringerBriefs in Computational Intelligence | Cham :Springer International Publishing :Imprint: Springer,2017Descripción: 1 recurso electrónico (X, 89 páginas); 34 ilustraciones., 21 ilustraciones en colorTipo de contenido:

texto

Tipo de medio:

computadora

Tipo de soporte:

recurso en línea

ISBN:

9783319539942

Tema(s):

Género/Forma:

Libros electrónicos.

Formatos físicos adicionales: Edición impresa:; Sin título; Sin título; Sin títuloClasificación CDD:

006.3
23

Recursos en línea:

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Contenidos:

Introduction -- Generalized Type-2 Fuzzy Logic -- Edge Detection Methods and Filters Used on Digital Image Processing -- Metrics for Edge Detection Methods -- Edge Detection Methods Based on Generalized Type-2 Fuzzy Logic Systems -- Generalized Type-2 Fuzzy Edge Detection Applied on a Face Recognition System -- Experimentation and Results Discussion -- Conclusions.

En: Springer eBooksResumen: 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.

Lista(s) en las que aparece este ítem: Libros Electrónicos

Existencias ( 1 )
Notas de título ( 2 )

Existencias
Tipo de ítem	Biblioteca actual	Colección	Signatura topográfica	Estado	Fecha de vencimiento	Código de barras
Libro Electrónico (LE)	Biblioteca Virtual	Colección Electrónica (CE)		Disponible		BIV0003276

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.