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Person Recognition System Based on a Combination of Body Images from Visible Light and Thermal Cameras
The experimental results show that the proposed person recognition method using the information extracted from body images is efficient for enhancing recognition accuracy compared to systems that use only visible light or thermal images of the human body.
Age estimation using a hierarchical classifier based on global and local facial features
Finger vein recognition using minutia‐based alignment and local binary pattern‐based feature extraction
A new finger vein recognition method using minutia‐based alignment and local binary pattern (LBP)‐based feature extraction, which reduces false rejection error and thus the equal error rate (EER) significantly.
Convolutional Neural Network-Based Finger-Vein Recognition Using NIR Image Sensors
A finger-vein recognition method that is robust to various database types and environmental changes based on the convolutional neural network (CNN) is proposed and showed a better performance compared to the conventional methods.
A brain–computer interface method combined with eye tracking for 3D interaction
Finger vein recognition using weighted local binary pattern code based on a support vector machine
- H. Lee, B. Kang, E. Lee, K. Park
- Computer ScienceJournal of Zhejiang University SCIENCE C
- 3 July 2010
This research proposes a new identification method of finger vascular patterns using a weighted local binary pattern (LBP) and support vector machine (SVM) and shows that the equal error rate (EER) is significantly lower compared to that without the proposed method or using a conventional method.
Real-Time Image Restoration for Iris Recognition Systems
A new real-time iris image-restoration method, which can increase the camera's depth-of-field (DOF) areas without requiring any additional hardware and shows that iris recognition errors when using the proposed restoration method were greatly reduced.
Multimodal biometric method that combines veins, prints, and shape of a finger
A new finger recognition method based on the score-level fusion of finger veins, fingerprints, and finger geometry features is proposed; its performance is better than the conventional Z-score normalization method and the equal error rate was lower than those of the other methods.
Image restoration of skin scattering and optical blurring for finger vein recognition