生物识别
质心
人工智能
计算机科学
模式识别(心理学)
相似性(几何)
融合
特征(语言学)
计算机视觉
字错误率
数学
图像(数学)
哲学
语言学
作者
Mohd Shahrimie Mohd Asaari,Shahrel Azmin Suandi,Bakhtiar Affendi Rosdi
标识
DOI:10.1016/j.eswa.2013.11.033
摘要
In this paper, a new approach of multimodal finger biometrics based on the fusion of finger vein and finger geometry recognition is presented. In the proposed method, Band Limited Phase Only Correlation (BLPOC) is utilized to measure the similarity of finger vein images. Unlike previous methods, BLPOC is resilient to noise, occlusions and rescaling factors; thus can enhance the performance of finger vein recognition. As for finger geometry recognition, a new type of geometrical features called Width-Centroid Contour Distance (WCCD) is proposed. This WCCD combines the finger width with Centroid Contour Distance (CCD). As compared with the single type of feature, the fusion of W and CCD can improve the accuracy of finger geometry recognition. Finally, we integrate the finger vein and finger geometry recognitions by a score-level fusion method based on the weighted SUM rule. Experimental evaluation using our own database which was collected from 123 volunteers resulted in an efficient recognition performance where the equal error rate (EER) was 1.78% with a total processing time of 24.22 ms.
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