A Face Recognition System Based on Back Propagation Neural Network Using Haar Wavelet Transform and Morphology

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 298)

Abstract

Today it is necessary to design an efficient security system which can protect unauthorized access on any system using extremely secure and excellent system for face recognition. In this paper, a robust face recognition system approach is proposed for image decomposition using Haar wavelet transform, feature detection using Successive Mean Quantization Transform (SMQT) and splipt up sparse network of window (SNoW) classifier and after detected face is sent for feature extraction using gray-scale morphology then extracted feature is sent for recognition using Backpropagation neural network which provide verification of face images. Average recall rate of up to 98.5 % for the database of 200 images. The efficiency of the proposed system obtained as 98.5 %. In This paper we use MATLAB to detect and recognize the respective face.

Keywords

Back propagation neural network (BPNN) Haar wavelet transform Face recognition SMQT features Snow classifier Gray-scale morphology 

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Copyright information

© Springer India 2014

Authors and Affiliations

  1. 1.Department of Computer EngineeringEngineering College BikanerBikanerIndia

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