• Manish Kumar
• Rahul Gupta
• Sumit Saini
• Abhishek Goel

In this research, we propose a novel face recognition approach which consist of both frame and texture information to represent face images. The whole area of face is partitioned into small blocks from which Local Binary Pattern (LBP) histograms are extracted and concatenated into a single image, the extracted enhanced feature histograms representing the given face image. On the bases of extracted features of face, give more weight of main part of face (like eyes, ear, and nose) on which recognition is performed by using nearest neighbour techniques. Analysis of results seemingly shows the perfection of the proposed scheme over all considered methods (PCA and Local Binary Pattern) on ORL database which include testing the efficiency of the proposed approach against lighting and aging of the faces. In addition to its simplicity and efficiency, the scheme requires very less time for feature extraction.

Eigen, Fisher face, conventional LBP, Binarization

"Novel Weighted LBP Approach for Face Recognition System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 4, page no.214-218, April-2018, Available :http://www.jetir.org/papers/JETIR1804044.pdf

"Novel Weighted LBP Approach for Face Recognition System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 4, page no. pp214-218, April-2018, Available at : http://www.jetir.org/papers/JETIR1804044.pdf