Fuzzy Approaches and Analysis in Image Processing

2017 ◽  
pp. 1-31 ◽  
Author(s):  
Ezhilmaran D ◽  
Adhiyaman M
Keyword(s):  
Neural Network ◽  
Image Processing ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Membership Functions ◽  
Significant Development ◽  
Diverse Field ◽  
Self Study

Fuzzy set theory originates to a great extent of interest among the researchers in past decades. It is a key tool to handle the imperfect of information in the diverse field. Typically, it plays a very important role in image processing and found the significant development in many active areas such as pattern recognition, neural network, medical imaging, etc. The use of fuzzy set theory is to tackle uncertainty in the form of membership functions when there is an image gray levels or information is lost. This chapter concerns the preliminaries of fuzzy, intuitionistic fuzzy, type-2 fuzzy and intuitionistic type-2 fuzzy set theory and its application in the fingerprint image; furthermore, the contrast enhancement and edge detection are carried out for that with the assistance of fuzzy set theory. It is useful to the students who want to self-study. This chapter composed just to address that issue.

Fuzzy Approaches and Analysis in Image Processing

2018 ◽  
pp. 511-542
Author(s):  
Ezhilmaran D ◽  
Adhiyaman M
Keyword(s):  
Neural Network ◽  
Image Processing ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Membership Functions ◽  
Significant Development ◽  
Diverse Field ◽  
Self Study

Fuzzy set theory originates to a great extent of interest among the researchers in past decades. It is a key tool to handle the imperfect of information in the diverse field. Typically, it plays a very important role in image processing and found the significant development in many active areas such as pattern recognition, neural network, medical imaging, etc. The use of fuzzy set theory is to tackle uncertainty in the form of membership functions when there is an image gray levels or information is lost. This chapter concerns the preliminaries of fuzzy, intuitionistic fuzzy, type-2 fuzzy and intuitionistic type-2 fuzzy set theory and its application in the fingerprint image; furthermore, the contrast enhancement and edge detection are carried out for that with the assistance of fuzzy set theory. It is useful to the students who want to self-study. This chapter composed just to address that issue.

A NOVEL APPROACH TO IMAGE THRESHOLDING BASED ON 2D HOMOGENEITY HISTOGRAM AND MAXIMUM FUZZY ENTROPY

2011 ◽  
Vol 07 (01) ◽  
pp. 105-133 ◽  
Author(s):  
H. D. CHENG ◽  
YANHUI GUO ◽  
YINGTAO ZHANG
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Pattern Recognition ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Fuzzy Entropy ◽  
Image Thresholding ◽  
Novel Approach ◽  
Entropy Principle

Image thresholding is an important topic for image processing, pattern recognition and computer vision. Fuzzy set theory has been successfully applied to many areas, and it is generally believed that image processing bears some fuzziness in nature. In this paper, we employ the newly proposed 2D homogeneity histogram (homogram) and the maximum fuzzy entropy principle to perform thresholding. We have conducted experiments on a variety of images. The experimental results demonstrate that the proposed approach can select the thresholds automatically and effectively. Especially, it not only can process "clean" images, but also can process images with different kinds of noises and images with multiple kinds of noise well without knowing the type of the noise, which is the most difficult task for image thresholding. It will be useful for applications in computer vision and image processing.

Multi-Attribute Decision Making Using Interval Type-2 Fuzzy AHP and Its Application on Borsa Istanbul (BIST)

2021 ◽  
pp. 30-56
Author(s):  
Beyza Ahlatcioglu Ozkok ◽  
Hale Gonce Kocken
Keyword(s):  
Decision Making ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Fuzzy Ahp ◽  
Short Review ◽  
Analytic Hierarchy ◽  
Multi Attribute Decision Making ◽  
Interval Type

Analytic hierarchy process (AHP) is a widely used multi-attribute decision-making (MADM) approach. Due to the complexity and uncertainty involved in real world problems, decision makers might be prefer to make fuzzy judgments instead of crisp ones. Furthermore, even when people use the same words, individual judgments of events are invariably subjective, and the interpretations that they attach to the same words may differ. This is why fuzzy numbers has been introduced to characterize linguistic variables. Fuzzy AHP methods have recently been extended by using type-2 fuzzy sets. Type-2 fuzzy set theory incorporates the uncertainty of membership functions into the fuzzy set theory. In this chapter, the authors firstly provide a short review on applications of interval type-2 fuzzy AHP on MADM problems. Then, they present a very efficient MADM technique, interval type-2 fuzzy AHP, to solve the portfolio selection problem that is to decide which stocks are to be chosen for investment and in what proportions they will be bought. And finally, they provided a case study on BIST.

scholarly journals Decision-Making Approach with Fuzzy Type-2 Soft Graphs

2020 ◽  
Vol 2020 ◽  
pp. 1-25
Author(s):  
Sundas Shahzadi ◽  
Musavarah Sarwar ◽  
Muhammad Akram
Keyword(s):  
Decision Making ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Mathematical Structure ◽  
Soft Set ◽  
Soft Sets ◽  
Research Article ◽  
Primary Relationship

Molodtsov’s theory of soft sets is free from the parameterizations insufficiency of fuzzy set theory. Type-2 soft set as an extension of a soft set has an essential mathematical structure to deal with parametrizations and their primary relationship. Fuzzy type-2 soft models play a key role to study the partial membership and uncertainty of objects along with underlying and primary set of parameters. In this research article, we introduce the concept of fuzzy type-2 soft set by integrating fuzzy set theory and type-2 soft set theory. We also introduce the notions of fuzzy type-2 soft graphs, regular fuzzy type-2 soft graphs, irregular fuzzy type-2 soft graphs, fuzzy type-2 soft trees, and fuzzy type-2 soft cycles. We construct some operations such as union, intersection, AND, and OR on fuzzy type-2 soft graphs and discuss these concepts with numerical examples. The fuzzy type-2 soft graph is an efficient model for dealing with uncertainty occurring in vertex-neighbors structure and is applicable in computational analysis, applied intelligence, and decision-making problems. We study the importance of fuzzy type-2 soft graphs in chemical digestion and national engineering services.

Spectral Parameters of Straightness Deviation Evaluation

2016 ◽  
Vol 876 ◽  
pp. 74-79
Author(s):  
Alexander Vladimirovich Glubokov ◽  
Svetlana Vladimirovna Glubokova ◽  
Alexey Vileninovich Shulepov ◽  
Sergey Evgenievich Ped
Keyword(s):  
Neural Network ◽  
Spectral Analysis ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Automated System ◽  
Spectral Parameters ◽  
Deviation Measurement

Spectral analysis of different profiles obtained during straightness deviation measurement was performed. The several profiles are showed, for which the value of straightness deviation is the same, but its behavior differs greatly. Spectral parameters characterizing the type of straightness deviation are proposed. The automated system based on factors of fuzzy-set theory with implementation in the form of neural network is developed.

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