A Fast and Robust Personal Identification Approach Using Handprint

Author(s):  
Jun Kong ◽  
Miao Qi ◽  
Yinghua Lu ◽  
Xiaole Liu ◽  
Yanjun Zhou
2013 ◽  
Vol 278-280 ◽  
pp. 1228-1231 ◽  
Author(s):  
Shuang Xu ◽  
Min Li ◽  
Ji Feng Ding ◽  
Yan Qiu Cui

This paper presents a new personal identification approach with fusion of hand shape geometry and palmprint features based on Gabor wavelet transformation. Two kinds personal features can be extracted form the low-resolution hand images. Hand shape geometry features include length of four fingers and width of palm. The palmprint features are composed of principal lines, wrinkles, minutiae, delta points. In pattern matching, the normalization method of matching degree is proposed. At the same time square difference distance is used to calculate feature matching degree of the hand shape geometry and palmprint. The result of experiment show that this approach is the most suitable, acceptable and the higher recognition rate, respectively, using different feature extraction methods.


2013 ◽  
Vol 2013 ◽  
pp. 1-13
Author(s):  
Chih-Yu Hsu ◽  
Pei-Shan Lee ◽  
Kuo-Kun Tseng ◽  
Yifan Li

Security certification is drawing more and more attention in recent years; the biometric technology is used in a variety of different areas of security certification. In this paper, we propose a palm image recognition method to identify an individual for vehicular application; it uses palm image as a key for detecting the car owner. We used mobile phone cameras to take palm images and performed a new identification approach by using feature regularization of palm contour. After identification is confirmed, the phone uses Bluetooth/WiFi to connect the car to unlock it. In our evaluation, the experiments show that our approach is effective and feasible.


AIAA Journal ◽  
1998 ◽  
Vol 36 ◽  
pp. 1479-1485
Author(s):  
Anil L. Salunkhe ◽  
Prasanna M. Mujumdar

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