基于细节点局部结构与LBP的指纹特征融合方法

摘要

Due to the small sensing area of fingerprint scanners,the absence of singular point and limited number of matched minutiae make matching partial fingerprint challenging.The performance can be improved by feature fusion which combines several impression of the same finger.A novel algorithm which combines local structures and local binary pattern (LBP) to get feature fusion was proposed.The super template could enlarge the valid area and increase the reliability of minutiae to overcome the disadvantage of small sensing area.The experimental results show that the proposed feature fusion scheme is effective in reducing FNMR of partial fingerprint matching.%针对指纹传感器图像采集面积小造成的奇异点缺失,匹配特征点较少等情况,文中提出了一种利用同一手指多幅图像,通过结合细节点邻域结构与局部二值模式(LBP)纹理特征生成合成模板以扩大注册模板的有效面积,同时提升模板中特征点可信度,从而匹配小面积指纹图像的方法.实验结果表明,本文提出的指纹特征融合方法能有效降低小面积指纹图像匹配的拒真率.