This repository contains Python framework for palmprint recognition using Convolutional Neural Networks, the main functionality is:
- learning filters from palmprint images
- learning embedding of the palmprint image into low dimensional feature vector
- learning binary classifier comparing couples of images
- dataset processing and result evaluation
Lasagne - CNN implementation (layers, objectives, ...)
Theano - CNN implementation (symbolic expressions, ...)
Seaborn - visualization
SciPy - image processing and visualization
Bob - biometrics (evaluation)
IITD model - trianed on the 1st half of the IITD dataset - leaves 2nd half for testing
Casia model - trained on the 1st half of the Casia dataset - leaves the 2nd half for testing
The two pre-trained models can be downloaded from here:
https://www.dropbox.com/s/gzv2heo9n43llfg/models.zip?dl=0
Casia touchless palmprint database (2D) (Info)
IITD touchless palmprint database (2D) (Info)
[1] R. Raghavendra and Ch. Busch - Texture based features for robust palmprint recognition: a comparative study
[2] Z. Sun, T. Tan, Y. Wang and Stan Z. Li - Ordinal Palmprint Represention for Personal Identification
[3] Q. Zheng, A. Kumar, and G. Pan - Suspecting Less and Doing Better: New Insights on Palmprint Identification for Faster and More Accurate Matching
[3] A. W. Kong and D. Zhang - Competitive Coding Scheme for Palmprint Verification
[4] V. Kanhangad, A. Kumar and D. Zhang - Contactless and Pose Invariant Biometric Identification Using Hand Surface
[5] A. Morales, M. A. Ferrer and A. Kumar - Towards contactless palmprint authentication
[6] H. Imtiaz, S. A. Fattah - A DCT-based Feature Extraction Algorithm for Palm-print Recognition
[7] A. Kumar - Incorporating Cohort Information for Reliable Palmprint Authentication
[8] D. Zhang, A. W. Kong, J. You and M. Wong - Online Palmprint Identification
[9] A. Kumar and H. C. Shen - Palmprint Identification Using PalmCodes
[10] A. W. Kong and D. Zhang - Feature-level Fusion for Effective Palmprint Authentication