Please use this identifier to cite or link to this item:
http://nopr.niscpr.res.in/handle/123456789/13991| Title: | A heuristic model for optimizing fuzzy knowledge base in a pattern recognition system |
| Authors: | Jamshidnezhad, Amir Nordin, Jan Md |
| Keywords: | Classifier;Facial expression recognition;Fuzzy system;Genetic algorithm (GA);Human Computer Interaction (HCI) System |
| Issue Date: | May-2012 |
| Publisher: | NISCAIR-CSIR, India |
| 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. |
| Page(s): | 341-347 |
| ISSN: | 0975-1084 (Online); 0022-4456 (Print) |
| Appears in Collections: | JSIR Vol.71(05) [May 2012] |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| JSIR 71(5) 341-347.pdf | 253.9 kB | Adobe PDF | View/Open |
Items in NOPR are protected by copyright, with all rights reserved, unless otherwise indicated.