融合全局和局部方向特征的掌纹识别方法

Palmprint Recognition Based on Fusing Global and Local Directional Features

掌纹识别是受到较多关注的生物特征识别技术之一。在各类掌纹识别的方法中,基于方向特征的方法取得了很好的效果。为了进一步提升识别精度,提出一种融合全局和局部方向特征的掌纹识别算法,主要融合了基于方向编码的方法、基于方向特征局部描述子的方法和结合方向特征和相关滤波器的方法。其中前2种方法属于空间域方法,可很好地提取掌纹的局部方向特征;而第3种方法属于频域方法,能有效地提取全局方向特征。在匹配值层对该3种方法的识别结果进行融合。本文算法在2个掌纹数据库上进行了验证,实验结果表明,本文方法的识别性能明显优于其他几种掌纹识别方法。

Palmprint recognition is one of the most popular biometrics identification technologies.Among the various methods of palmprint recognition,the method based on directional features has achieved good results.In order to further improve the recognition accuracy,a palmprint recognition algorithm combining global and local directional features is proposed,which mainly combines the method based on directional coding,the method based on local descriptor of directional features and the method of combining directional features and correlation filters.The first two methods belong to the spatial domain method,which can extract the local directional features of the palmprint.The third method belongs to the frequency domain method,which can effectively extract the global directional features.The recognition results of the three methods are merged at the score level.The algorithm is validated on two palmprint databases.The experimental results show that the recognition performance of this method is better than other palmprint recognition methods.