NDLI: Image description by Hierarchical Prioritised Fuzzy Systems

Content Provider	IEEE Xplore Digital Library
Author	Salgado, P. Garrido, P.
Copyright Year	2009
Description	Author affiliation: CITAB - Universidade de Trás-os-Montes e Alto Douro, 5001-801 Vila Real, Portugal (Salgado, P.) \|\| Algoritmi Research Centre, Universidade do Minho, 4800 Guimarães, Portugal (Garrido, P.)
Abstract	The inherently hierarchical problem of evaluating the complexity of an image interpretation is of relevance in both computer science and cognitive psychology. In this paper a new method of rule generation for the Hierarchical Prioritized Fuzzy System, HPFS, is proposed, which overcomes the problem of lack of interpretability of most of the traditional fuzzy systems in modelling image. A hierarchical structure of different fuzzy systems is presented in this work based on prioritising, through the use of a relevance measure of a fuzzy system. For this hierarchical structure we propose a new algorithm to be used in two learning phases: structure building and parametric identification. This new fuzzy modelling technique automatically generates and tunes the sets of fuzzy rules in the Hierarchical Prioritized Fuzzy Structure. The learning strategy performs the division of the learning data among the various levels of the hierarchical structure. The effectiveness of the proposed method is tested on cross image recognition.
Starting Page	173
Ending Page	178
File Size	311465
Page Count	6
File Format	PDF
ISBN	9781424453108
DOI	10.1109/ICCCYB.2009.5393940
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-01-26
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fuzzy logic Fuzzy sets Image recognition Merging Hierarchical systems Collaboration Clustering algorithms Parametric statistics Cybernetics Fuzzy systems
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Fuzzy Clustering Approaches Based on AFS Fuzzy Logic I

Color image segmentation using multiscale fuzzy C-means and graph theoretic merging

Evolutionary fuzzy clustering

Study of Aggregation Operators for Scheduling Clusters in Digital Images of Plants

Image description and primitive extraction using fuzzy sets

On Dynamic Clustering and Two Options

Fuzzy clustering of fuzzy systems

Fuzzy-logic based information fusion for image segmentation

A hierarchical segmentation for image processing

Image description by Hierarchical Prioritised Fuzzy Systems

Similar Documents

Fuzzy Clustering Approaches Based on AFS Fuzzy Logic I

Color image segmentation using multiscale fuzzy C-means and graph theoretic merging

Evolutionary fuzzy clustering

Study of Aggregation Operators for Scheduling Clusters in Digital Images of Plants

Image description and primitive extraction using fuzzy sets

On Dynamic Clustering and Two Options

Fuzzy clustering of fuzzy systems

Fuzzy-logic based information fusion for image segmentation

A hierarchical segmentation for image processing

Image description by Hierarchical Prioritised Fuzzy Systems