PCA Based Rapid and Real Time Face Recognition Technique

Authors

  • Chandrashekar TR Department of MLE, Sri Siddhartha Institute of Technology, Tumkur, Karnataka, India
  • ShivaKumar KB Department of TCE, Sri Siddhartha Institute of Technology, Tumkur, Karnataka, India
  • G A Srinidhi Department of TCE, Sri Siddhartha Institute of Technology, Tumkur, Karnataka, India
  • Goutam AK S D College of Engineering, Muzaffarnagar, Uttar Pradesh, India

Keywords:

Biometrics, Face Detection, Eigen Face

Abstract

Economical and efficient that is used in various applications is face Biometric which has been a popular form biometric system. Face recognition system is being a topic of research for last few decades. Several techniques are proposed to improve the performance of face recognition system. Accuracy is tested against intensity, distance from camera, and pose variance. Multiple face recognition is another subtopic which is under research now a day. Speed at which the technique works is a parameter under consideration to evaluate a technique. As an example a support vector machine performs really well for face recognition but the computational efficiency degrades significantly with increase in number of classes. Eigen Face technique produces quality features for face recognition but the accuracy is proved to be comparatively less to many other techniques. With increase in use of core processors in personal computers and application demanding speed in processing and multiple face detection and recognition system (for example an entry detection system in shopping mall or an industry), demand for such systems are cumulative as there is a need for automated systems worldwide. In this paper we propose a novel system of face recognition developed with C# .Net that can detect multiple faces and can recognize the faces parallel by utilizing the system resources and the core processors. The system is built around Haar Cascade based face detection and PCA based face recognition system with C#.Net. Parallel library designed for .Net is used to aide to high speed detection and recognition of the real time faces. Analysis of the performance of the proposed technique with some of the conventional techniques reveals that the proposed technique is not only accurate, but also is fast in comparison to other techniques.

References

PAUL VIOLA, MICHAEL J. JONES, ―Robust RealTime Face Detection,‖ International Journal of Computer Vision 57(2), 137–154, 2004.

Cheng-Chin Chiang,Wen-Kai Tai,Mau-Tsuen Yang,Yi-Ting Huang,Chi-Jaung Huang, ―A novel method for detecting lips,eyes and faces in real time,‖ Elsevier, Real-Time Imaging , 2003.

Gregory Shakhnarovich Paul A. Viola Baback Moghaddam, ―A Unified Learning Framework for Real Time Face Detection and Classification,‖

B.A. Efraty, M. Papadakis, A. Profitt, S. Shah and I.A. Kakadiaris, ―Facial Component-Landmark Detection,‖

Panagiotis Perakis, Georgios Passalis, Theoharis Theoharis and Ioannis A. Kakadiaris, ―3D Facial Landmark Detection & Face Registration A 3D Facial Landmark Model & 3D Local Shape Descriptors Approach,‖ CGL Technical Report, No. TP-2010-01, 2010.

Amit Jain, Jeffrey Huang and Shiaofen Fang, ―Gender Identification Using Frontal Facial Images,‖ IEEE, 2005

Prinshul Jain, ―Automatic Human Gender Identification System,‖ A Master Thesis, IIT kanpur, 2008

Alessandro Cellerino , Davide Borghetti, Ferdinando Sartucci, ―Sex differences in face gender recognition in humans,‖ Brain Research Bulletin, Elsevier,2004.

Zhiwei Zhua, Qiang Jib, ―Robust real-time eye detection and tracking under variable lighting conditions and various face orientations,‖ Computer Vision and Image Understanding, 2005.

M. Hassaballah, Kenji Murakami, Shun Ido, ―An Automatic Eye Detection Method for Gray Intensity Facial Images,‖ IJCSI International Journal of Computer Science Issues, Vol. 8, Issue 4, No 2, 2011.

Young H. Kwon and Niels da Vitoria Lobo, ―Age Classification from Facial Images, Computer Vision and Image Understanding,‖ Vol. 74, No. 1, April, pp. 1–21, 1999.

Carlos Busso, Zhigang Deng , Serdar Yildirim, Murtaza Bulut, Chul Min Lee, Abe Kazemzadeh, Sungbok Lee, Ulrich Neumann, Shrikanth Narayanan, ―Analysis of Emotion Recognition using Facial Expressions, Speech and Multimodal Information,‖ ICMI’04, October 13–15, 2004.

Aruna Chakraborty, Amit Konar, Uday Kumar Chakraborty, and Amita Chatterjee, ―Emotion Recognition From Facial Expressions and Its Control Using Fuzzy Logic,‖ IEEE Transactions on Systems, Man, and Cybernetics—Part a: Systems and Humans, vol. 39, no. 4, July 2009.

Downloads

Published

2024-02-26

How to Cite

Chandrashekar, T. R., ShivaKumar, K. B., G A, S., & Goutam, A. K. (2024). PCA Based Rapid and Real Time Face Recognition Technique. COMPUSOFT: An International Journal of Advanced Computer Technology, 2(12), 385–390. Retrieved from https://ijact.in/index.php/j/article/view/67

Issue

Section

Original Research Article

Similar Articles

1 2 3 4 5 6 7 > >> 

You may also start an advanced similarity search for this article.