A fuzzy qualitative approach for scene classification

Chern Hong Lim, Chee Seng Chan

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

10 Citations (Scopus)

Abstract

Scene classification has been studied extensively in the recent past. Most of the state-of-the-art solutions assumed that scene classes are mutually exclusive. However, this is not true as a scene image may belongs to multiple classes and different people are tend to respond inconsistently even given a same scene image. In this paper, we propose a fuzzy qualitative approach to address this problem. That is, we first adopted the fuzzy quantity space to model the training data. Secondly, we present a novel weight function, w to train a fuzzy qualitative scene model in the fuzzy qualitative states. Finally, we introduce fuzzy qualitative partition to perform the scene classification. Empirical results using a standard dataset and a comparison with K-nearest neighbour has shown the effectiveness and robustness of the proposed method.

Original languageEnglish
Title of host publication2012 IEEE International Conference on Fuzzy Systems, FUZZ 2012
DOIs
Publication statusPublished - 2012
Externally publishedYes
EventIEEE International Conference on Fuzzy Systems 2012 - Brisbane, Australia
Duration: 10 Jun 201215 Jun 2012
Conference number: 21st
https://ieeexplore.ieee.org/xpl/conhome/6241469/proceeding (Proceedings)

Publication series

NameIEEE International Conference on Fuzzy Systems
ISSN (Print)1098-7584

Conference

ConferenceIEEE International Conference on Fuzzy Systems 2012
Abbreviated titleFUZZ-IEEE 2012
CountryAustralia
CityBrisbane
Period10/06/1215/06/12
Internet address

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