Facial Expression Recognition Using Local Binary Patterns with Different Distance Measures

  • Sarika Jain
  • Sunny Bagga
  • Ramchand HablaniEmail author
  • Narendra Chaudhari
  • Sanjay Tanwani
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 243)


Facial expression recognition is a well-known activity in the domain of human–computer interaction and computer vision. In this work, we have applied face detection algorithm on the images to get the facial part only; then, we have used local binary pattern (LBP) operator to get the facial features. Finally, to match the test image with the different expressions, various distance measures which are Euclidian distance, taxicab distance, chessboard distance, Bray-Curtis distance and chi-square distance have been applied. The maximum facial expression recognition rate of Bray-Curtis distance measure reaches 92.85 % for person-dependent expression recognition, which is better than other distance measures. The experiments were performed on JAFFE which is a standard dataset, and result shows that the facial expression recognition with LBP and Bray-Curtis for person-dependent recognition is an effective method.


Facial expression Local binary patterns Distance measures Person-dependent expression recognition 


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Copyright information

© Springer India 2014

Authors and Affiliations

  • Sarika Jain
    • 1
  • Sunny Bagga
    • 1
  • Ramchand Hablani
    • 1
    Email author
  • Narendra Chaudhari
    • 2
  • Sanjay Tanwani
    • 3
  1. 1.Computer Science DepartmentSanghvi Institute of Management and ScienceIndoreIndia
  2. 2.Computer Science and EngineeringIndian Institute of TechnologyIndoreIndia
  3. 3.Computer Science and EngineeringSchool of Computer Science and IT DAVVIndoreIndia

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