聚类优化贝叶斯算法在手背静脉识别中的应用研究

Application of Bayesian algorithm in the back of the hand vein recognition Clustering Optimization

手背静脉识别是近几年来新发展起来的一种新兴生物识别方法 ,是目前身份认证领域关注的热点之一。手背静脉拥有很好的唯一性和普遍性,但在采样阶段和识别阶段中,仍存在识别率不高和效率较低等问题,因此解决准确性与效率等问题将成为将此技术投入应用的关键。贝叶斯算法虽在识别领域有着广泛应用,但是若逐个识别效率低下,文章将针对常用的几种不同图像分割算法进行讨论,并结合聚类优化后的贝叶斯算法,来提高大数据量情况下手背静脉识别的准确性以及效率。

The back of the hand vein recognition is a new method of biometrics in recent years, newly developed, it is one of the hot areas of concern authentication. It has a very good hand vein uniqueness and universality, but the sampling phase and the recognition phase, there is still the recognition rate is not high and low efficiency and other issues, so as to their accuracy and efficiency to solve the problem will be put into application of this technology The essential. Although Bayesian algorithm is widely used in the field of identification, but one by one if the low recognition efficiency, the article will discuss several different commonly used for image segmentation algorithm, combined with optimized Bayesian clustering algorithm to improve the large amount of data the case of hand vein recognition accuracy and efficiency.