A heuristic model for optimizing fuzzy knowledge base in a pattern recognition system

Amir Jamshidnezhad, Md. Jan Nordin

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

This study presents a genetic algorithm (GA) to optimize performance of a fuzzy system for reconition of facial expression from images. In proposed model, a Mamdani-type fuzzy rule based system recognizes emotions, and a GA is used to improve accuracy and robustness of the system. To evaluate system performance, images from FG-Net (FEED) and Cohn-Kanade database were used to obtain the best functions parameters. Proposed model under training process not only increased accuracy rate of emotion recognition but also increased validity of the model in adverse conditions.

Original languageEnglish
Pages (from-to)341-347
Number of pages7
JournalJournal of Scientific and Industrial Research
Volume71
Issue number5
Publication statusPublished - May 2012

Fingerprint

Pattern recognition systems
Genetic algorithms
Knowledge based systems
Fuzzy rules
Fuzzy systems

Keywords

  • Classifier
  • Facial expression recognition
  • Fuzzy system
  • Genetic algorithm (GA)
  • Human computer interaction (HCI) system

ASJC Scopus subject areas

  • General

Cite this

A heuristic model for optimizing fuzzy knowledge base in a pattern recognition system. / Jamshidnezhad, Amir; Nordin, Md. Jan.

In: Journal of Scientific and Industrial Research, Vol. 71, No. 5, 05.2012, p. 341-347.

Research output: Contribution to journalArticle

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