An Improved Face Recognition Approach using Principal Component Analysis

Deepak Gaur; Raj Kumar Sagar

doi:https://doi.org/10.51976/ijari.231404

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An Improved Face Recognition Approach using Principal Component Analysis

Deepak Gaur, Raj Kumar Sagar

Vol 2 , Issue 3 , July - September 2014 | Pages: 15-25 | Research Paper

https://doi.org/10.51976/ijari.231404

Received: July 20, 2014 | Revised: July 30, 2014 | Accepted: August 20, 2014 | Published Online: September 15, 2014

Author Details ( * ) denotes Corresponding author

1. * Deepak Gaur, Department of Computer Science & Application, ASET, Amity University, Noida, Uttar Pradesh, India (India.dgaur@amity.edu)

2. Raj Kumar Sagar, Department of Computer Science & Application, ASET, Amity University, Noida, Uttar Pradesh, India

Due to digitization and for security purpose a lot of research has been going on in the wide area of affect computing. One of the field under this affect computing is to recognize the human faces with maximum accuracy. There are still large numbers of difficulties to recognize the accurate facial expression. In this research paper we are going to represent our experimental results for facial recognition by using Principal Component Analysis (PCA) algorithm. So in the first section of this paper we discussed some algorithm for facial recognition, than compare our results of research with these algorithm. We took Extended Cohn-Kanade Dataset(CK+) for experimental results. Our experimental results are implemented in OpenCV.

Keywords

Affect Computing; Face recognition; Principal Component Analysis; Open CV; Cohn-Kanade DataSet

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