Face Recognition Using PCA and Bit-Plane Slicing
The objective of the paper is face recognition using PCA and Bit plane slicing. It made a study on the dimensionality reduction on bit plane of images for face recognition. The proposed frame work would aid in robust design of face recognition system and
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Face Recognition Using PCA and Bit-Plane Slicing T. Srinivas, P. Sandeep Mohan, R. Shiva Shankar, Ch. Surender Reddy and P. V. Naganjaneyulu
Abstract The objective of the paper is face recognition using PCA and Bit plane slicing. It made a study on the dimensionality reduction on bit plane of images for face recognition. The proposed frame work would aid in robust design of face recognition system and addressed the challenging issues like pose and expression variation on ORL face database. It is in contrast to PCA on the image the design of PCA on bit plane reduces computation complexity and also reduces time. In the proposed frame work image is decomposed with the help of bit plane slicing, the feature have been extracted from the principle component analysis (PCA). Keywords PCA
Bit-plane slicing Feature extraction Face recognition
T. Srinivas (&) P. Sandeep Mohan R. Shiva Shankar Sri Venkateswara Engineering College, Suryapet, India e-mail: [email protected] P. Sandeep Mohan e-mail: [email protected] R. Shiva Shankar e-mail: [email protected] Ch. Surender Reddy R.R.S College of Engineering and Technology, Muthangi, India e-mail: [email protected] P. V. Naganjaneyulu PNC and Vijai Institute of Engineering and Technology, Phirangipuram, India e-mail: [email protected]
V. V. Das (ed.), Proceedings of the Third International Conference on Trends in Information, Telecommunication and Computing, Lecture Notes in Electrical Engineering 150, DOI: 10.1007/978-1-4614-3363-7_60, Ó Springer Science+Business Media New York 2013
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60.1 Introduction Basically face recognition can be used for verification and Identification. In the year 1988 Kirby and Sirovich applied PCA, a standard linear algebra technique for the face recognition problem. The technique was the landmark and considered as milestone because it requires only less than one hundred values in code a normalized face images accurately. For the past few years, a systematic investigation has been going on to design a robust security/authentication mechanism. With the advent of miniaturized imaging systems the design process of security systems has been improved. The devices are application specific and present data (Biometric) to be incorporated into the design. Many researchers showed that the features extracted from face images aid in designing robust security/authentication systems. Successful face recognition system [1] is proposed utilizing Eigen face approach. This method is conventional, considers frontal and high contrast faces for implementing the system, but in real time faces may not be frontal and device intrinsic capture (illumination variation) properties pose difficulties in the process of detection. Thus in security and other computer vision applications, pose and variation in illuminations plays a critical role. The Eigen face approach is not satisfactorily addressing these problems. In recent works [2–4], face recognition is carried out with PCA method and succeeded well, but it fails as in
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