Palmprint Recognition across Different Devices

Sensors

Wei Jia¹  Rong-Xiang Hu¹  Jie Gui²  Yang Zhao² 

[1] Institute of Nuclear Energy Safety Technology, Chinese Academy of Science, Hefei 230031, China; E-Mail:;Institute of Intelligent Machines, Chinese Academy of Science, Hefei 230031, China; E-Mails:

关键词: biometrics;    palmprint recognition;    different devices;    sensors;   

DOI  :  10.3390/s120607938

来源: mdpi

【 摘 要 】

In this paper, the problem of Palmprint Recognition Across Different Devices (PRADD) is investigated, which has not been well studied so far. Since there is no publicly available PRADD image database, we created a non-contact PRADD image database containing 12,000 grayscale captured from 100 subjects using three devices, i.e., one digital camera and two smart-phones. Due to the non-contact image acquisition used, rotation and scale changes between different images captured from a same palm are inevitable. We propose a robust method to calculate the palm width, which can be effectively used for scale normalization of palmprints. On this PRADD image database, we evaluate the recognition performance of three different methods, i.e., subspace learning method, correlation method, and orientation coding based method, respectively. Experiments results show that orientation coding based methods achieved promising recognition performance for PRADD.

【 授权许可】

CC BY   
© 2012 by the authors; licensee MDPI, Basel, Switzerland.