This paper presents feature level fusion approach using multi resolution Curvelet transform for face and palm biometrics.In this paper feature extraction has been done by taking the curvelet transform of bit quantized images.The curvelet coefficient thus obtained acts as feature set for classification.The five sets of coefficients from five different versions of images are used to train five SVMs.During testingthe results of SVMs of palm and face are fused in a single column feature vector to determine the final classification.The results of fusion are compared with that of unimodal biometric system of palm and face separately.Using a common feature extraction method for both unimodal and fusion helps in analyzing the efficiency of recognition.The experimental results show that the proposed scheme out performs the unimodal biometrics using curvelet transform.All the experiments are carried out on two well-known data bases AT&T for face and POLY U for palm print images.

 

Published In : IJCSN Journal Volume 3, Issue 1

Date of Publication : 01 February 2014

Pages : 116 - 120

Figures : 03

Tables : 01

Publication Link : IJCSN-2014/3-1/Feature-Fusion-of-Palm-and-Face-Based-on-Curvelet-Transform

 

 

 

Prof G. Seshikala : is a resident of Bangalore, Karnataka. She received BE degree from Vijayanagara Engineering college, Gulbarga University, Karnataka, India in 1987, M.E degree from SDMCET, Dharwad, Karnataka, India in 1997. Presently she is working as prof in department of ECE in Atria Institute of Technology, Bangalore,Karnataka, India. Her field of research are Biomedical Signal processing, Pattern recognition, processing and Biometrics.

Dr. U.P Kulkarni : is a resident of Dharwad town of Karnataka, India.Hereceived B.E degree from Gogete Institute of Technology, Belgaum ,karnataka, India in1989, M.Tech degree from PSG College of Technology,Coimbatore, Tamil Nadu, India in 1992 and PhD degree from ShivajiUniversity, Kolhapur,India in 2007. Presently he is working as Professor and head indepartment of Computer Science & Engineering, Dharwad, India. Hisresearch areas are Ubiquitous computing and Network Applications Multi agents Systems.

Dr. M. N. Giri Prasad : is native of Hindupur town of Anantapur District ofAndhra Pradesh, India. He received B.Tech degree from J.N.T UniversityCollege of Engineering, Anantapur, Andhra Pradesh, India in 1982, M.Techdegree from Sri Venkateshwara University, Tirupati, Andhra Pradesh, India in1994 and PhD degree from J.N.T University, Hyderabad, Andhra Pradesh, India in 2003. Presently he is working as Professor and Head, department ofElectronics and communication at JNTUA University Anantapur, Andhra Pradesh, India. His research areas are WirelessCommunications and Biomedical Instrumentation.

 

 

 

 

 

 

 

Face biometrics

Palm biometrics

Multimodal biometrics

Feature level fusion

In this paper a multimodal biometric system based on feature level fusion of palm and face is presented. The face and palm has rich information in its features and are user friendly traits and can be used for feature level fusion. Using a common feature extraction technique for both unimodal and multimodal the performance of biometric fusion is well analyzedthe results obtained for multimodal biometrics out performs the unimodal. Further improvement in the system can be carried using reduction techniques for classifiers.

 

 

 

 

 

 

 

 

 

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