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Fuzzy Logic for Image Processing : A Gentle Introduction Using Java.

By: Contributor(s): Material type: TextTextSeries: SpringerBriefs in Electrical and Computer Engineering SeriesPublisher: Cham : Springer International Publishing AG, 2016Copyright date: ©2017Edition: 1st edDescription: 1 online resource (141 pages)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783319441306
Subject(s): Genre/Form: Additional physical formats: Print version:: Fuzzy Logic for Image ProcessingDDC classification:
  • 006.42
LOC classification:
  • TK5102.9
Online resources:
Contents:
Intro -- Preface -- Contents -- About the Authors -- Part I Fundamentals of Fuzzy Image Processing -- 1 Image Representation Using Java -- 1.1 Introduction -- 1.2 Gray-Level Images -- 1.3 Color Models -- 1.4 Color Image Representation Using Java -- References -- 2 Low-Level Image Processing -- 2.1 Introduction -- 2.2 Contrast Enhancement -- 2.2.1 Gray-Level Transformation -- 2.2.2 Thresholding -- 2.2.3 Histogram Transformation -- 2.3 Image Smoothing -- 2.4 Edge Detection -- 2.4.1 Canny Operator -- 2.4.2 Optimization-Based Operators -- References -- 3 Basics of Fuzzy Logic -- 3.1 Introduction -- 3.2 Fuzzy Set Theory -- 3.3 Fuzzy Rule-Based Systems -- 3.3.1 Fuzzification -- 3.3.2 Fuzzy Rule Base and Inference Engine -- 3.3.3 Defuzzification -- 3.4 Fuzzy Models -- 3.4.1 Design of Fuzzy Rule-Based Systems -- 3.4.2 Neuro-Fuzzy Models -- References -- 4 Fuzzy Image Processing -- 4.1 Introduction -- 4.2 Image Fuzzification -- 4.2.1 Fuzzy Image -- 4.3 Image Defuzzification -- 4.4 Fuzziness Measures -- References -- 5 Java for Image Processing -- 5.1 Basic Concepts -- 5.2 Java for Image Processing -- 5.3 Applet -- 5.4 ImageJ -- 5.4.1 Macros -- 5.4.2 Plugins -- 5.5 Fuzzy Systems in Java -- References -- Part II Application to Image Processing -- 6 Color Contrast Enhancement -- 6.1 Introduction -- 6.2 Multichannel Image Processing -- 6.3 Fuzzy Techniques for Color Enhancement -- 6.4 A Fuzzy Rule-Based System for Color Enhancement -- 6.5 Example: Natural Image Enhancement -- References -- 7 Image Segmentation -- 7.1 Introduction -- 7.2 The Segmentation Problem -- 7.3 Methods for Segmentation -- 7.3.1 Crisp Clustering -- 7.3.2 Fuzzy Clustering -- 7.3.3 Spatial Fuzzy Clustering -- 7.4 Example: Color Segmentation -- 7.5 Example: Texture Segmentation -- References -- 8 Morphological Analysis -- 8.1 Mathematical Morphology -- 8.1.1 Morphological Operators.
8.2 Fuzzy Morphology -- 8.3 Example: Biological Image Segmentation -- References -- 9 Image Thresholding -- 9.1 Introduction -- 9.2 Otzu Method -- 9.3 Fuzzy Thresholding -- 9.4 Example: Document Image Analysis -- 9.4.1 Document Segmentation -- 9.4.2 Region Classification -- References -- Appendix A Java Code References -- Index.
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Intro -- Preface -- Contents -- About the Authors -- Part I Fundamentals of Fuzzy Image Processing -- 1 Image Representation Using Java -- 1.1 Introduction -- 1.2 Gray-Level Images -- 1.3 Color Models -- 1.4 Color Image Representation Using Java -- References -- 2 Low-Level Image Processing -- 2.1 Introduction -- 2.2 Contrast Enhancement -- 2.2.1 Gray-Level Transformation -- 2.2.2 Thresholding -- 2.2.3 Histogram Transformation -- 2.3 Image Smoothing -- 2.4 Edge Detection -- 2.4.1 Canny Operator -- 2.4.2 Optimization-Based Operators -- References -- 3 Basics of Fuzzy Logic -- 3.1 Introduction -- 3.2 Fuzzy Set Theory -- 3.3 Fuzzy Rule-Based Systems -- 3.3.1 Fuzzification -- 3.3.2 Fuzzy Rule Base and Inference Engine -- 3.3.3 Defuzzification -- 3.4 Fuzzy Models -- 3.4.1 Design of Fuzzy Rule-Based Systems -- 3.4.2 Neuro-Fuzzy Models -- References -- 4 Fuzzy Image Processing -- 4.1 Introduction -- 4.2 Image Fuzzification -- 4.2.1 Fuzzy Image -- 4.3 Image Defuzzification -- 4.4 Fuzziness Measures -- References -- 5 Java for Image Processing -- 5.1 Basic Concepts -- 5.2 Java for Image Processing -- 5.3 Applet -- 5.4 ImageJ -- 5.4.1 Macros -- 5.4.2 Plugins -- 5.5 Fuzzy Systems in Java -- References -- Part II Application to Image Processing -- 6 Color Contrast Enhancement -- 6.1 Introduction -- 6.2 Multichannel Image Processing -- 6.3 Fuzzy Techniques for Color Enhancement -- 6.4 A Fuzzy Rule-Based System for Color Enhancement -- 6.5 Example: Natural Image Enhancement -- References -- 7 Image Segmentation -- 7.1 Introduction -- 7.2 The Segmentation Problem -- 7.3 Methods for Segmentation -- 7.3.1 Crisp Clustering -- 7.3.2 Fuzzy Clustering -- 7.3.3 Spatial Fuzzy Clustering -- 7.4 Example: Color Segmentation -- 7.5 Example: Texture Segmentation -- References -- 8 Morphological Analysis -- 8.1 Mathematical Morphology -- 8.1.1 Morphological Operators.

8.2 Fuzzy Morphology -- 8.3 Example: Biological Image Segmentation -- References -- 9 Image Thresholding -- 9.1 Introduction -- 9.2 Otzu Method -- 9.3 Fuzzy Thresholding -- 9.4 Example: Document Image Analysis -- 9.4.1 Document Segmentation -- 9.4.2 Region Classification -- References -- Appendix A Java Code References -- Index.

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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.

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