A Novel Algorithm for Human Facial Expression Recognition using Gabor Filter and Eigenvector | Zendy

Poonam Dhankhar | Zendy; Neha Sahu | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

A Novel Algorithm for Human Facial Expression Recognition using Gabor Filter and Eigenvector

Author(s) -

Poonam Dhankhar,

Neha Sahu

Publication year - 2014

Publication title -

international journal of computer applications

Language(s) - English

Resource type - Journals

ISSN - 0975-8887

DOI - 10.5120/17018-7300

Subject(s) - computer science , gabor filter , expression (computer science) , facial expression recognition , pattern recognition (psychology) , eigenvalues and eigenvectors , artificial intelligence , gabor wavelet , filter (signal processing) , facial expression , computer vision , algorithm , facial recognition system , image (mathematics) , physics , quantum mechanics , programming language , discrete wavelet transform , wavelet transform , wavelet

Facial Expression Recognition has always been topic of interest for research in field of human computer/machine interaction based on machine learning and image processing tools. However, the inaccuracy of such systems is always challenging. Hence to resolve this problem, a novel algorithm using Gabor Filter and Eigenvector Based Distributed Feature, is proposed in this paper. The work is enhancement of existing Face Identification by covering the challenges of Facial Expression. The approach combines face recognition along with facial expression recognition. Over the time authentication system is replaced by biometric authentication. These systems are based on some human features and behavior. The mean accuracy is improved to 93.4%. The effectiveness and stability is shown in experimental results of the algorithm.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research