A Neural Network based Facial Expression Recognition using Fisherface

نویسندگان

  • Zaenal Abidin
  • Agus Harjoko
چکیده

Facial expression plays significant role for human beings to communicate their emotions. Automatic facial expression analysis is a flourishing area of research in computer science, and it is also still a challenge. This paper discusses the application of a natural network based facial expression recognition using fisherface. Back propagation neural network is used as a classifier for classifying the expressions. For face portion segmentation and localization, integral projection method is used. The accuracy of system performance have evaluated on a public database “Japanese Female Facial Expression (JAFFE)”. The experimental results show the effectiveness of our scheme. The best average recognition rate achieves 89.20%. General Terms Image Processing, Pattern Recognition

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تاریخ انتشار 2012