Bee royalty offspring algorithm for improvement of facial expressions classification model

Amir Jamshidnezhad, Md. Jan Nordin

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

A major issue which divides the facial expressions from the other classification domains is complicated behaviour of human to express the emotions which should be recognised with the classifier model. Existing research recognise the emotions using a range of classification techniques. However, low accuracy rate, large training set, large extracted features or priority for sequence images are the main drawbacks of those works. One of the recent techniques to address the facial expressions problem is fuzzy rule-based system (FRBS) which is used as a successful method to model and solve the natural-based problems. However, FRBS is poor to adapt the existing knowledge with the diverse conditions. In this article a novel hybrid genetic-fuzzy rule-based model is proposed to optimise the performance of fuzzy classification while the limited raw input data as the features are used. In this model, the proposed genetic algorithm simulates the honey bees offspring generation process called bee royalty offspring algorithm (BROA) to improve the training process of classic genetic algorithm. The comparison results illustrated that the genetic-fuzzy classification model improves considerably the accuracy rate and performance of FRBS while the BROA modify the training process of genetic-based algorithms.

Original languageEnglish
Pages (from-to)175-191
Number of pages17
JournalInternational Journal of Bio-Inspired Computation
Volume5
Issue number3
DOIs
Publication statusPublished - 2013

Fingerprint

Facial Expression
Fuzzy rules
Fuzzy Rule-based Systems
Knowledge based systems
Fuzzy Classification
Genetic algorithms
Genetic Algorithm
Model
Comparison Result
Image Sequence
Fuzzy Rules
Large Set
Divides
Classifiers
Express
Classifier
Optimise
Range of data
Training
Emotion

Keywords

  • Bee royalty offspring algorithm
  • BROA
  • Classification
  • Facial expressions recognition
  • FRBS
  • Fuzzy rule-based system
  • Genetic algorithms

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Bee royalty offspring algorithm for improvement of facial expressions classification model. / Jamshidnezhad, Amir; Nordin, Md. Jan.

In: International Journal of Bio-Inspired Computation, Vol. 5, No. 3, 2013, p. 175-191.

Research output: Contribution to journalArticle

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