Person Recognition by Hilbert Pair of Wavelets using Facial Images

Abstract

In human identification, the face acts as an important tool that carries the identity of each person. The human mind has the ability to re-cognize faces after the first view of a human face. Though there are many types of face detection/recognition system found no method can give the 100% accurate outputs. In this proposed system we are implementing and analyzing a new method that can be used for person recognition system that can produce better output accuracies. In the proposed system of person recognition method, one of the robust wavelet transform methods is used for the extraction of the features from the original images. The wavelet type used is known as the Dual Tree M-Band Wavelet Transform (DTMBWT) method. Using this transform the low and high sub-bands is obtained. These low and high sub-band coefficients are given as the input for the classification purpose. The sub-band obtained from the DTMBWT transform is given as the inputs for the classification purpose. The classification process is done using the K-Nearest Neighbor (KNN) classifier scheme. The system is implemented by using the facial images from the ORL database. By using this dataset images the performance measures of the proposed system is calculated in the form of graphical results such as Receiver Operating Characteristic (ROC), Inverse ROC and Expected Performance Curve (EPC) curves. Results show that proposed DTMBWT based face recognition provides better results than other approaches.