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Edge Detection Methods Based on Generalized Type-2 Fuzzy Logic

  • Claudia I. Gonzalez
  • Patricia Melin
  • Juan R. Castro
  • Oscar Castillo

Part of the SpringerBriefs in Applied Sciences and Technology book series (BRIEFSAPPLSCIENCES)

Also part of the SpringerBriefs in Computational Intelligence book sub series (BRIEFSINTELL)

Table of contents

  1. Front Matter
    Pages i-x
  2. Claudia I. Gonzalez, Patricia Melin, Juan R. Castro, Oscar Castillo
    Pages 1-2
  3. Claudia I. Gonzalez, Patricia Melin, Juan R. Castro, Oscar Castillo
    Pages 3-9
  4. Claudia I. Gonzalez, Patricia Melin, Juan R. Castro, Oscar Castillo
    Pages 11-16
  5. Claudia I. Gonzalez, Patricia Melin, Juan R. Castro, Oscar Castillo
    Pages 17-19
  6. Claudia I. Gonzalez, Patricia Melin, Juan R. Castro, Oscar Castillo
    Pages 21-35
  7. Claudia I. Gonzalez, Patricia Melin, Juan R. Castro, Oscar Castillo
    Pages 37-41
  8. Claudia I. Gonzalez, Patricia Melin, Juan R. Castro, Oscar Castillo
    Pages 43-75
  9. Claudia I. Gonzalez, Patricia Melin, Juan R. Castro, Oscar Castillo
    Pages 77-78
  10. Back Matter
    Pages 79-89

About this book

Introduction

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.

Keywords

Computational Intelligence Pattern Recognition Edge Detection Methods Face Recognition Digital Image Processing Sobel Edge Detection

Authors and affiliations

  • Claudia I. Gonzalez
    • 1
  • Patricia Melin
    • 2
  • Juan R. Castro
    • 3
  • Oscar Castillo
    • 4
  1. 1.School of EngineeringUniversity of Baja CaliforniaTijuanaMexico
  2. 2.Division of Graduate StudiesTijuana Institute of TechnologyTijuanaMexico
  3. 3.School of EngineeringUniversity of Baja CaliforniaTijuanaMexico
  4. 4.Division of Graduate StudiesTijuana Institute of TechnologyTijuanaMexico

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-53994-2
  • Copyright Information The Author(s) 2017
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-319-53993-5
  • Online ISBN 978-3-319-53994-2
  • Series Print ISSN 2191-530X
  • Series Online ISSN 2191-5318
  • Buy this book on publisher's site
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