基于手指静脉和手指轮廓的个性化融合方法

Personalized Fusion Method Based on Finger Vein and Finger Contour

近年来手指静脉识别成为一种有前途的身份验证技术.采集图像时,手指的姿势或光照的变化会严重影响算法的性能.多生物特征识别可以在一定程度上克服这些限制,提高识别性能.相比其他的生物特征融合,手指静脉和手指轮廓融合的优点是采集图像比较方便,只需要手指静脉采集设备即可获得这两种生物特征的图像.基于此,提出了一种基于手指静脉和手指轮廓的个性化加权融合识别方法.首先根据原始得分对样本进行分类,然后依据分类结果求得样本的分类置信度得分.相比原始得分,分类置信度得分加入了分类信息,能够为后面的融合提供更多的有效信息.最后,为了体现个体之间的差异,使用个性化权重将分类置信度得分进行融合.在自建数据库上的实验结果验证了该方法的有效性.

Finger vein is a promising biometric for the authentication due to its some advantages. However, when capturing the finger vein image, the pose variation of the finger or the illumination variation may cause failure to verification. To overcome these limitations of using a single biometric, multiple biometrics can be combined to improve the performance. Compared with the fusion of other biometrics, the advantage of the fusion of finger vein and finger contour is that acquiring the two biometric image is convenient because the finger vein image and finger contour image can be obtained by a finger vein capturing device. In this paper, we propose a personalized fusion method based on finger vein and finger contour at the score level. The samples are firstly classified based on the original matching score, and then the classification confidence score （CCS） can be obtained based on the classification result. Compared with the traditional score, CCS contains additional classification information which may provide more useful information for the final fusion. In addition, a more effective personalized weight fusion based on CCS is proposed due to the difference of different subjects. Finally, we conduct extensive experiments on our database to evaluate the effectiveness of our proposal.