Home
Call For Papers
Submission
Author
Registration
Publications
About
Contact Us

  Subspace Based Face Recognition using Clustering  
  Authors : Elumalai Gokulakrishnan; Seshasayanam Asha
  Cite as:

 

The main theme of this research proposal is about how the face recognition takes place in real-time. In this paper we are going to focus two things mainly artificial neural network (ANN) and Clustering for face detection and face recognition. Artificial neural network provides an optimal solution for face recognition. Unsupervised learning algorithm and self-organized map (SOM) is used for feature based face recognition. We are going to train such an artificial neural network to extract facial features even for identical twins.to recognize fast in template database we are going to use clustering technique to achieve better performance. In face recognition twins cannot be identified still research is going on. I proposed solution for identifying twins that might give a better result.

 

Published In : IJCSN Journal Volume 3, Issue 5

Date of Publication : October 2014

Pages : 318 - 320

Figures : 05

Tables : 01

Publication Link : Subspace Based Face Recognition using Clustering

 

 

 

Elumalai Gokulakrishnan : School Of Computing Science and Engineering, VIT University-Chennai. Chennai, India

Seshasayanam Asha : School Of Computing Science and Engineering, VIT University-Chennai. Chennai, India

 

 

 

 

 

 

 

ANN

SOM

Neuron

FRR

FAR

Biometrics provides a high level security end-to-end system supports worldwide. Face recognition provides a better security solution. Nowadays artificial neural networks plays a vital role for learning algorithm it provides an optimal performance output.in this research we discussed about how the face recognition works in real time using ANN.I strongly recommend the this technique for future face recognition. The Generation should be “Identify Everyone, Everywhere all the time” [7]. Still there are some more problem for face recognition in future the face recognition must provide without any faulty to recognize people confidentiality.

 

 

 

 

 

 

 

 

 

[1] “A Subspace-Based Multi-View Face Clustering And Recognition Approach”, M Alarmel Mangai, N.Ammasai Gounden, IEEE 2011.

[2] “On The Use Of Mobile Phone And Biometrics For Accessing Restricted Web Service”, Carlos Vivaracho, IEEE 2012.

[3] “A Sequential Subspace Face Recognition Framework Using Genetic-Based Clustering”, Deng Zhang, Shingo Mabu, Feng Wen, IEEE 2011.

[4] “Clustering-Based Discriminative Locality Alignment For Face Gender Recognition”, Duo Cheng, Jun Cheng, Dacheng Tao, IEEE 2012.

[5] “Background Removal Using K-Means Clustering as a Preprocessing Technique for DWT Based Face Recognition”, surabhi A.R, Shwetha T Parekh, IEEE 2011.

[6] “Co-Learned Multi-View Spectral Clustering for Face Recognition Based on Image Sets”, Likun Huang, Yap-peng tan, IEEE 2014.

[7] http://techcrunch.com/2013/06/29/tomorrowssurveillance/.

[8] “Face Recognition Technology “, Mittal Rao, LasKhitha Parmar,IJICT 2013.