Automatic Emotion Detection


  • Zala Hiranba Computer Science & Engineering, SLTIET
  • Pansuriya Nirali -
  • Jajal Aayushi Computer Science & Engineering, SLTIET
  • Rabadiya Dhara -


pre-processing, feature extraction, projection profile, recognition, Genetic Algorithm, Neural network


Facial expressions analysis most significant part for human computer interaction. Now days, face emotion
recognition is most important application of computer vision that can be used for security, entertainment and human
machine interface. Automatic face emotion recognition is still challenging & emerging problem with many applications
such an automatic surveillance, robot motion, video indexing and retrieval and monitoring systems. Emotion
recognition and classification depends upon gesture, pose, facial expression, speech and behavioral reactions, etc. In
this paper, an automatic emotion recognition and classification method is based on Genetic Algorithm and on neural
network. This system consists of 3 steps which automatically detect the face emotion image: First, pre-processing such
as adjusting contrast, colour segmentation, filtering, and edge detection is applied on the input image. Secondly,
features are extracted with projection profile method due to high speed which has taken as processed input image.
Finally, in third stage to compute optimized parameters of eyes and lip through the GA, then emotions (neutral, happy,
sad, dislike, angry, surprise and fear) is classified using artificial neural network. The proposed system is tested on a
face emotion image. The obtained results show that better performance of genetic algorithm along with neural network.



How to Cite

Zala Hiranba, Pansuriya Nirali, Jajal Aayushi, & Rabadiya Dhara. (2016). Automatic Emotion Detection. International Journal of Advance Research in Engineering, Science & Technology, 3(13), -. Retrieved from