Feature Extraction of Human Facail Expressions Using Haar Wavelet and Neural network | ||
| Iraqi Journal of Science | ||
| Article 1, Volume 57, Issue 2, March 2016, Pages 1558-1565 | ||
| Authors | ||
| Salah Sleibi Al-Rawi; Ahmed T. Sadiq; Wasan M. Alaluosi | ||
| Abstract | ||
| One of the challenging and active research topics in the recent years is Facial Expression. This paper presents the method to extract the features from the facial expressions from still images. Feature extraction is very important for classification and recognition process. This paper involve three stages which contain capture the images, pre-processing and feature extractions. This method is very efficient in feature extraction by applying haar wavelet and Karhunen-Loève Transform (KL-T). The database used in this research is from Cohen-Kanade which used six expressions of anger, sadness fear, happiness, disgust and surprise. Features that have been extracted from the image of facial expressions were used as inputs to the neural network to recognize the facial expression .The recognition rate in this research was 90.5%. | ||
| Keywords | ||
| Facial expressions; Haar Wavelet; L Transform; Features extraction; Neural network | ||
|
Statistics Article View: 195 PDF Download: 19 |
||