{'fraction_non_alphanumeric': 0.029469548133595286, 'fraction_numerical': 0.0029469548133595285, 'mean_word_length': 4.85632183908046, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A Novel Contactless Multimodal Biometric System Based on Multiple Hand Features

This paper proposes a novel multimodal biometric system based on multiple hand features, i.e. palmprint, palm vein, palm dorsal vein, finger vein and hand geometry. In this system, the palmprint, palm vein and dorsal vein images are firstly captured using an integrated contactless acquisition device. And then these images are preprocessed and split into six regions of interest (ROIs), that is, one palmprint ROI, one palm vein ROI, three finger vein ROIs and one dorsal vein ROI. After that, features are extracted from each ROI and matched respectively. Besides these features, hand geometry feature is also extracted from the original palm vein image and matched. Finally, these matching scores are fused to make the final score for decision. Experiments on a large data set show that the proposed system can get a very high accuracy (the EER is around 0.01%), which outperforms any uni-modal system based on single feature of hand.