Fuzzy Set Similarity HISTOGRAM THRESHOLDING
2.2. Fuzzy Set Similarity
Distinguishing similar groups or classifying similar elements needs a tool for deciding the similarity degree among them. Similarity measurement of two fuzzy sets A dan B, indicates the degree of similarity of two fuzzy sets. The idea of finding the similarity of such fuzzy sets is regarding the goodness of separability of the two fuzzy sets resulted, when we used a gray level as the threshold value. The lower the measured similarity value, the larger the separability of the two fuzzy sets. The center of the object region is used as a seed for starting the similarity measure process. Since all gray levels less than this value considered as the member of the object region, we do not need to measure their similarity to the other fuzzy set, because their membership to the other fuzzy set should be zero. Also, we define the center of the background region as a seed for ending the similarity measure process as depicted in Fig. 1. Since all gray levels larger than this value are considered as the member of objects region, we do not need to consider their membership grade to the other fuzzy set. To this end, a similarity measure of two fuzzy sets is used for assessing the separability of the resulted fuzzy sets when we choose a gray level as the threshold. We assign gray level x i of the two fuzzy regions, which existed between v B and v O , membership values µ B x i and µ O x i to the fuzzy sets B and O, respectively. The more the difference of membership values of x i to the fuzzy sets B and O, the better separability of the two fuzzy sets. Hence, for the two fuzzy sets B and O, at a particular gray level x i , we measure the information amount for discrimination of µ B x i to µ O x i [9]. In this paper, the information amount for discrimination at gray level x i DiscT, x i , which used T as the threshold value, is defined as . 6 , i B i O x x i e x T Disc µ µ − = a b c d Figure 3. The thresholded images by the proposed method a b c d Figure 2. The original images. Information and Communication Technology Seminar, Vol. 1 No. 1, August 2005 ISSN 1858-1633 2005 ICTS 192 The reason for calculating from the absolute value is only to consider the difference membership degree of each gray level to the two fuzzy sets. It is obvious that the least difference for gray level at which its membership to the two fuzzy sets has the same value is achieved in the intersection point between two lines reflecting the membership value in the fuzzy region.2.3. Criterion Function
Parts
» INTRODUCTION ICTS2005 The Proceeding
» Opening Fundamental Operations of Mathematical Morphology
» Morphological filter Filter theorem
» Granulometry and size distribution
» PGPC texture model and estimation of the optimal structuring element: The PGPC
» CONCLUSIONS ICTS2005 The Proceeding
» Non-ergodicity parameters RESULTS AND DISCUSSIONS 1 Partial structure factors and
» SIMULATIONS CONCLUSION ICTS2005 The Proceeding
» IMAGE RECONSTRUCTION SYSTEM DESIGN
» RESULT CONCLUSION ICTS2005 The Proceeding
» MULTI-RESOLUTION HISTOGRAM TECHNIQUE DATA
» VALIDATION STRATEGY RESULTS AND DISCUSSION
» CONCLUSION ICTS2005 The Proceeding
» INTRODUCTION DISTILATION COLUMN AND ARTIFICIAL NEURAL NETWORK
» Using Temperature Correlation Using Flow Rate Correlation
» INTRODUCTION DETECTION OF SINGLE TREE FELLING WITH SOFT
» Supervised Fuzzy c-means Method
» Neural Network classification METHOD 1. Datasets
» Neural Network Classification Results
» Comparison of Classification Results
» DISCUSSIONS ICTS2005 The Proceeding
» CONCLUSION ACKNOWLEDGEMENT ICTS2005 The Proceeding
» Caching Access List BANDWIDTH MANAGEMENT IMPLEMENTATION
» Rate Limiting BANDWIDTH MANAGEMENT IMPLEMENTATION
» BANDWIDTH MANAGEMENT CONCEPTS RESULT
» The Architecture of UML Elements Model Element
» Diagram Element Editing SYSTEM ARCHITECTURE
» Server Application Architecture Undo
» INTRODUCTION IMPLEMENTATION TESTING ICTS2005 The Proceeding
» INTRODUCTION E-PURSE ICTS2005 The Proceeding
» Interfaces Verification Tool POS – Smart Card
» MULTI AGENT SYSTEM MAS A WEIGHTED-TREE SIMILARITY ALGORITHMS
» RESULTS ICTS2005 The Proceeding
» Facial Animation Morphing and Deformation Cross Dissolve
» Feature Morphing Mesh Morphing Text-to-Speech TTS Basic Block
» Text-to-Video Algorithm Text-To-Video Stake And Desain
» Suggestion CONCLUSION AND SUGGESTION 1 Conclusion
» The Concept SHARE-IT SYSTEM ARCHITECTURE
» SHARING SCENARIO CONCLUSION ICTS2005 The Proceeding
» The Bayesian Network Model and Modified Bayesian Optimization
» Designs and Implementation SCHEDULING MODEL AND IMPLEMENTATION
» Comparison Proposed Schedule with Real Schedule
» Face-to-Face Technique Long Distance Technique
» Scenario to motivate. Context_Selection Applikasi.
» INTRODUCTION ARCHITECTURE. CONCLUSION. ICTS2005 The Proceeding
» SUGGESTION ICTS2005 The Proceeding
» Data Flow Database Structure
» EXPERIMENTAL RESULT ICTS2005 The Proceeding
» Investment Stock Prototyping System Design
» Database Model Stock Valuation
» INTRODUCTION METHODOLOGY ICTS2005 The Proceeding
» Buffer Overrun Cryptography Random Numbers
» Anti-Tampering Error Handling Injection Flaws
» Encapsulate Field Restructuring Arrays
» Generating Secure Random Number Storing Deleting Passwords
» Smart Serialization Message Digest
» Convert Message with Private Key to Public Key
» INTRODUCTION CURRENT STATUS ICTS2005 The Proceeding
» INTRODUCTION PROPOSED SIMULATION MODEL
» PARALLELIZATION STRATEGY ICTS2005 The Proceeding
» EXPERIMENTS AND DISCUSSION CONCLUSION
» INTRODUCTION RESULTS AND DISCUSSION
» EXPERIMENTAL ICTS2005 The Proceeding
» RESULT AND DISCUSSION ICTS2005 The Proceeding
» Color segmentation SYSTEM CONFIGURATION
» FEATURE CHARACTERISTICS AND GENERAL RULE
» EXPERIMENTAL RESULT CONCLUSION ICTS2005 The Proceeding
» INTRODUCTION REVIEW OF LITERATURE
» Social Economics Impact. Restructuring Impact
» Manager Application Mobile Agent Generator MAG Mobile Agents MAs
» SNMP Table Polling SNMP Table Filtering
» BREAST CARCINOMA TUMOR ICTS2005 The Proceeding
» WATERSHED ALGORITHM METHODS ICTS2005 The Proceeding
» RESULT AND DISCUSION ICTS2005 The Proceeding
» FADED INFORMATION FIELD ARCHITECTURE
» ALGORITHMS TO CHOOSE NODES TO CREATE THE FADED
» SYSTEM SIMULATIONS ICTS2005 The Proceeding
» Model and Teory MODEL, TEORY, DESIGN, IMPLEMENTATION AND
» INTRODUCTION ANALYSIS AND RESULT
» INTRODUCTION A SIMPLE MODEL OF THE QUEUING SYSTEM
» SIMULATION RESULTS DISCUSSION ICTS2005 The Proceeding
» CONCLUSION INTRODUCTION ICTS2005 The Proceeding
» Dialog Processing ADDING NONVERBAL BEHAVIOUR
» Emotion Expression Experiment ADDING NONVERBAL BEHAVIOUR
» NATURAL LANGUAGE PROCESSING EMOTION REASONING
» Fuzzy Logic Control FLC System Planning
» Digital To Analog Converter DAC Motor Driver Position Sensor Display Unit
» INTRODUCTION CONCLUSION ICTS2005 The Proceeding
» Variable-Centered Rule Structure VARIABLE-CENTERED INTELLIGENT RULE SYSTEM
» Knowledge Refinement VARIABLE-CENTERED INTELLIGENT RULE SYSTEM
» Knowledge Building VARIABLE-CENTERED INTELLIGENT RULE SYSTEM
» Knowledge Inferencing VARIABLE-CENTERED INTELLIGENT RULE SYSTEM
» INTRODUCTION BASIC CONCEPTS OF FUZZY SETS
» Calculation of the Fitness Degree
» ESTIMATING MULTIPLE NULL VALUES IN RELATIONAL
» Chen’s [6] Result This Improving Method’s Result
» The Fuzzy Set HISTOGRAM THRESHOLDING
» Fuzzy Set Similarity HISTOGRAM THRESHOLDING
» EXPERIMENTAL RESULTS ICTS2005 The Proceeding
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