Exploring Various Aspects of Gabor Filter in Classifying Facial Expression

  • Seetha ParameswaranEmail author
  • Murali Parameswaran
  • Shelbi Joseph
  • Daleesha M. Viswanathan
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 656)


Facial expression detection is a well-studied domain in which facial features are extracted and then classified into six common expressions. One of the most common techniques used for extracting features is the Gabor filter. In literature, for extracting the features, the combined magnitude and phase values of the Gabor filter are used. This paper is exploring the performance of methods using the combined filtering method, using magnitude alone and using phase alone in the domain of facial expression detection. It is observed that considering phase values with the support vector machine classifier yielded an additional 8% accuracy when compared to combined methods.


Facial expression recognition Gabor wavelets Gabor magnitude Gabor phase Feature extraction Support vector machine Classification 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Seetha Parameswaran
    • 1
    Email author
  • Murali Parameswaran
    • 2
  • Shelbi Joseph
    • 1
  • Daleesha M. Viswanathan
    • 1
  1. 1.Cochin University of Science and TechnologyCochinIndia
  2. 2.Ramrao Adik Institute of TechnologyNavi MumbaiIndia

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