Publish In
International Journal of Advances in Computer Science and Cloud Computing (IJACSCC)-IJACSCC
Journal Home
Volume Issue
Volume-1,Issue-1  ( May, 2013 )
Paper Title
Enhanced K-Means Based Facial Expressions Recognition System
Author Name
Tanvi Sheikh, Shikha Agrawal
CSE Department CSIT Durg , Assistant Professor CSE Department CSIT Durg
Automatic facial expression recognition is an interesting and active research topic for research in the recent years. Facial expression recognition plays a vital role in Human Computer Interaction. Facial expressions are one of the key features of facial recognition. In this research work, Enhanced K-Means algorithm is proposed for classification of facial expressions from frontal facial images. To classify the expressions, algorithm uses two features: density of pixels and ratio of height to width of cropped boundary regions. The recognition system comprises preprocessing, feature extraction and expression classification. Based on the features extracted, Enhanced K-Means algorithm will classify the expressions into one of the expressions happy, sad and neutral. Expression classification will apply on the dataset of 200 images of KDEF (Karolinska Directed Emotional Face Database) database and expected to improve the performance of existing recognition system.
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