Three measures for secure palmprint identification
Pattern Recognition
Palmprint recognition with improved two-dimensional locality preserving projections
Image and Vision Computing
Personal Recognition Using Single-Sensor Multimodal Hand Biometrics
ICISP '08 Proceedings of the 3rd international conference on Image and Signal Processing
A Comparative Study of Palmprint Recognition Algorithms
ACM Computing Surveys (CSUR)
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Recently, there are keen interests in EigenPalm, which, collectively, refers to those methods that extract palmprint features directly from the appearance by means of Principal Component Analysis (PCA) for (dis)similarity matching. Encouraging results have been reported with the use of EigenPalm. However, we find a different story under a system and evaluation perspective. In this paper, we would like to introduce three issues that should be considered: the effects of templates from two different sessions, the effects of identical twins and the effects of unseen subjects. They are missing in the previous studies of EigenPalm.