International Journal of Advanced Computing and Communication Systems

The Novel Approach towards Face Detection by Corner Detection Using Special Morphological Masking System and Fast Algorithm

Tumpa Dey, Department of IT & CSE M.B.B College, Agartala, India.

Dibyendu Ghoshal, Department of ECE & EIENIT, Agartala, India.

International Journal of Advanced Computing and Communication Systems

Received On :

Revised On :

Accepted On :

Published On :

Volume 06, Issue 01

Page No :020-025

Abstract

In this work we have performed a face recognition technique using corner detection algorithm. Here we have used fast corner detection algorithm but modified it by applying a masking technique to make a robust technique with respect to noise. This paper describes twelve facial landmarks which include left eye corners, right eye corners, left eyebrows, right eyebrows, lip corners, nostrils. It consists of two parts; in the first step we have done the masking technique to filter the image from noise. In the second step we applied the fast corner detection algorithm to detect the facial landmarks. The Fast corner detector works on the corner response function (CRF), which is computed as a minimum change of intensity over all possible direction. Lastly we have done a comparison study with other filtering techniques with respect to proposed masking technique. In this paper, we have done the experiments using IRIS face Database, BioID and Cohn Kanade Database. Recognition rate achieved by applying the proposed method are very well.

Keywords

Face Recognition; facial landmarks; fast corner detection; masking technique; corner response function; IRIS face database; BioID database; Cohn kanade database .

Cite this Article

Tumpa Dey and Dibyendu Ghoshal, “The Novel Approach towards Face Detection by Corner Detection Using Special Morphological Masking System and Fast Algorithm, ”International Journal of Advanced Computing and Communication Systems, pp. 001-008, March 2019.

Copyright

© 2019 Tumpa Dey and Dibyendu Ghoshal. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.