Hand Vein Recognition with Bag of SIFT Feature Model
- https://doi.org/10.2991/icmmita-16.2016.255How to use a DOI?
- Vein Recognition; SIFT; Mismatching; BOSF; SVM
SIFT, which is widely used for feature extraction in image recognition task especially when image rotation, translation, uneven illumination occur, has been applied in vein recognition task more widely. However, mismatching between intra-class and inter-class, which is unbearable for personal identification task, is unavoidable under the traditional ratio-based matching framework. To solve such problem, the paper proposes bag of SIFT feature (BOSF) model to realize SIFT feature based matching framework from the perspective of feature coding and classification. Finally, the proposed approach is rigorously evaluated on the self-built database and achieves the state-of-the-art EER (Equal Error Rate) of 0.026%, which demonstrates the effectiveness of the proposed model.
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Fuqiang Li AU - Tongzhuang Zhang AU - Yong Liu PY - 2017/01 DA - 2017/01 TI - Hand Vein Recognition with Bag of SIFT Feature Model BT - Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications PB - Atlantis Press SP - 1078 EP - 1083 SN - 2352-538X UR - https://doi.org/10.2991/icmmita-16.2016.255 DO - https://doi.org/10.2991/icmmita-16.2016.255 ID - Li2017/01 ER -