Open Access Open Access  Restricted Access Subscription or Fee Access

Neural Network Associated with Recognition of Facial Expressions of Basic Emotions

Rehmat Khan, Rohit Raja


In the field of image processing, it is very interesting to recognize the human gesture for general life applications. For example, observing the gesture of a driver when he/she is driving and alerting him/her when in sleepy mood will be quite useful. Human gestures can be identified by observing the different movements of eyes, mouth, nose and hands. The face is a rich source of information about human behavior. The proposed method will recognize the facial expression from a well captured image. The approach for Facial Expression Recognition System is based on PCA and Neural Network. For any Facial Expression Recognition, it is necessary to extract the features of face that can be possibly used to detect the expression. For Feature Extraction the Principal Component Analysis will be used. After extracting the features the eigenvectors will be generated this will be further fed into the Neural Network for Expression Recognition. The paper briefly describes the schemes for selecting the image and then processing the image to recognize the expressions.


Eigen Faces Eigen Vector, Eigen Value, Neural Network, Back Propagation, Facial Expression Recognition System, FERS.

Full Text:



K. Susheel, Shitala,Vijay, R C Tripathi, ―Real Time Face Recognition Using Adaboost Improved Fast PCA Algorithm‖- IJAIA, Vol.2, No.3, July 2011

Avinash Kaushal, J P S Raina, ―Face detection using Neural Network and Gabor Wavelet Transform‖, IJCST Vol. 1, Issue 1, September 2010

Jagdish Lal Raheja, Umesh Kumar, ―Human facial expression detection from detected in capture image using back propagation neural network‖-IJCSIT, Vol.2, No.1, February 2010.

Amit Kumar, Prashant Sharma, Shishir Kumar, ―Face Recognition using Neural Network and Eigen values with Distinct Block Processing‖- IJCTT,Vol.1,2010.

Irene Kotsia and Ioannis Pitas,, ―Facial Expression Recognition in Image Sequences Using Geometric Deformation Features and Support Vector Machines‖- IEEE Transactions On Image Processing, Vol. 16, No. 1, January 2007.

Shishir Bashyal, Ganesh K. Venayagamoorthy , ―Recognition of facial expressions using Gabor wavelets and learning vector quantization‖- Engineering Applications of Artificial Intelligence ,12 November 2007

L. Ma and K. Khorasani, ―Facial Expression Recognition Using Constructive Feed forward Neural Networks‖, IEEE Transactions On Systems, Man, And Cybernetics—part B: Cybernetics, Vol. 34, No. 3, June 2004

Ming-Hsuan Yang, David J. Kriegman, and Narendra Ahuja, ― Detecting faces in Images:A survey‖, IEEE Transactions On Pattern Analysis And Machine Intelligence, Vol. 24, No. 1, January 2002

Mehrabian, A. (1981) Silent messages: Implicit communication of emotions and attitudes.Belmont,CA.(

[Mitchell, 1997] Mitchell, T.M., 1997. Artificial neural networks. In Mitchell, T.M. Machine learning. McGraw-Hill Science/Engineering/Math. pp.81-126.

P.Ekman and W.Friesen, The Facial Action Coding System , Consulting psychologists Press, SanFrancisco, CA,1978


  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.