An Efficient Facial Features Extraction Technique for Face Recognition System Using Local Binary Patterns
C.Nagaraju1, B.Srinu2, E. Srinivasa Rao3

1Dr. C. Nagaraju, Associate Professor, YSR College of Engineering of YV University, Poddutur (A.P), India.
2Mr. B. Srinu, Assistant Professor, Department of IT, Gayathri Vidya Parishad College of Engineering, Visakhapatnam (A.P), India.
3E. Srinivasa Rao, M.Tech, SE, Department of IT, Gayathri Vidya Parishad College of Engineering, Visakhapatnam (A.P), India.
Manuscript received on 10 May 2013 | Revised Manuscript received on 18 May 2013 | Manuscript Published on 30 May 2013 | PP: 76-78 | Volume-2 Issue-6, May 2013 | Retrieval Number: F0791052613/13©BEIESP
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Abstract: Imaging in life and materials sciences has become completely digital and this transformation of visual imagery in to mathematical constructs has made it common place for researchers to utilize computers for their day to day image analysis tasks. The main objective of the paper is extracting the facial features of an image. In this paper presents a survey on the recent use of Local Binary Patterns (LBPs) for face recognition. It is becoming a popular technique for face representation. In the existed system we are using LBP. It is a non-parametric kernel which summarizes the local special structure of an image and it is invariant to monotonic gray-scale transformations. Here, we describe the LBP technique and different approaches proposed in the literature to represent and to recognize faces but it is having some limitations like it is not suitable for shadow images and low contrasted images. To overcome those problems in this project we are proposing 2D principles of component analysis (2D-pca) to extract the facial features of an image. Here we are using our own data bases to extract the facial features.
Keywords: LBP, Extended LBP, PCA Kerne.

Scope of the Article: Pattern Recognition