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Histogram Based Face Recognition

C. H. Srinivasa Reddy*, G.Ravi Kumar**, S. Chinni Krishna Reddy***

*-** Assistant Professor, Vignan's Institute of Information Technology, Andhra Pradesh, India.

*** PG Scholar, Vignan's Institute of Information Technology, Andhra Pradesh, India.

Periodicity:October - December'2017
DOI : https://doi.org/10.26634/jip.4.4.14162

Abstract

Human face conveys more information about identification, expression, and emotions of a person. In today's world every individual in the society wants to be more secure from unauthorized authentication. In order to provide more security, “Facial Recognition” has come into the picture and lead a most challenging role of detecting the face with more accurate results without any false identities. To increase the efficiency of the face recognition, histogram based facial recognition is chosen, where a face region is fragmented into a number of regions and histogram values are extracted and they are linked together into a single vector. This vector is compared for the similarities between the facial images and provides a most efficient outcome.

Keywords

Face Recognition, Local Binary Pattern Histogram (LBPH), Histograms, Feature Extractions, Classification.

How to Cite this Article?

Reddy, S., Kumar, G.R. and Reddy, C.K. (2017). Histogram Based Face Recognition. i-manager’s Journal on Image Processing, 4(4), 31-35. https://doi.org/10.26634/jip.4.4.14162

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