动态分数选择的多视角非接触指纹识别融合

与传统的二维指纹采集方式相比,非接触的指纹采集方式可以提供更丰富的特征,并能克服二维采集方式某些不足．基于多视角非接触指纹识别融合问题,提出了基于聚类的动态分数选择(CDSS)算法．首先,通过聚类将匹配分数分为两类,分别计算两类中匹配分数的个数以及其他统计量,然后通过参数的判断选择相应的统计量作为整个系统最终用于决策的匹配分数．实验表明:相比单视角非接触二维指纹识别,基于CDSS的多视角非接触指纹识别的识别性能有显著提高．与sum、max、SVM和Fisher线性判别算法等的实验比较也验证了CDSS在多视角非接触指纹识别融合方面的优越性．

Dynamic score selection for multi-vision touchless fingerprint recognition fusion

Touchless fingerprint capturing can provide richer features and overcome the deficiency of 2D fingerprint recognition. In this paper, a clustering-based dynamic score selection (CDSS) algorithm is proposed for the combination of scores which are generated by different vision touchless fingerprint recognition systems. First, the scores are divided into two classes and the number of elements in each class and other statistic variables is computed. Then appropriate statistic value is chosen as the score for final decision of the whole system. The experimental results show that the performance of CDSS-based multi-vision touchless system can be enhanced efficiently compared to touchless fingerprint recognition and better than those of sum, max, SVM and Fisher linear discrimination algorithms.