基于连续分布方向图和改进的Poincaré Index的指纹分类  

Fingerprint Classification Based on Both Continuously Distributed Directional Image and Modified Version of Poincaré Index

作　　者：聂桂军[1] 吴陈[2] 叶锡君[3] 徐荣青[2] 

机构地区：[1]扬州环境资源职业技术学院计算机系,江苏扬州225007 [2]江苏科技大学中科院计算所智能计算开放实验室,江苏镇江212003 [3]南京农业大学信息科技学院,江苏南京210095

出　　处：《电子学报》2006年第5期947-952,共6页Acta Electronica Sinica

基　　金：江苏省教育厅自然科学基金(No.2002316)

摘　　要：本文提出了指纹连续分布方向图(场)的概念及其算法,连续分布方向图具有很好的连续性、渐变性、抗噪性和较高的精确度;对经典的PoincaréIndex计算公式和指纹奇异点检测算法进行了改进,改进后的PoincaréIndex不仅能精确表示向量场的旋转角度,而且还能精确表示向量场的旋转方向,能够在像素级水平精确定位指纹奇异点(core点和delta点).在此基础上,提出了一种新的基于连续分布方向图和改进的PoincaréIn-dex的5类自动指纹分类算法,在江苏科技大学指纹库(含4000幅指纹)上的分类结果表明,本算法能抗任意角度的指纹图像旋转,成功地解决了指纹分类中的图像平移、旋转和形变不变性问题,分类正确率达到97.05%,具有较好的健壮性,满足实用要求.A new concept on the continuously dislxibuted directional image/field （CDDF） and the method to compute it in the fingerprint images are proposed, which exhibits not only good continuity, well gradualness, and excel- lent robustness to the noises, but very high precision, as well. Then, the classical formula to compute the Poincare Index and the algorithm for the singularity detection are improved, so that the modified version of Poincare Index can present not only the rotation degrees, but also the rotation direction of the vector in the vector field, exactly. Therefore, it is able to locate the singularities （core points, and delta points） at pixel level with an accuracy of only one pixel. Based on these, a novel fingerprint classification algorithm based on both the continuously dislxibuted directional image and the modified version of Poincare Index is developed finally, which classifies input fingerprints into 5 categories ： arch, tented arch,left loop, right loop, and whorl. The experimental results obtained on the fingerprint database of Jiangsu University of Science and Technology demonstrate that this algorithm is invariant to image rotation of any degrees, and successfully solves the problem of image rotation, translation, and transformation in fingerprint classification. For the 4,000 images in this database, a classification accuracy of 97.05% for the five-class problem has been achieved. So it has better classification performance than previously reported in the literature.

关 键 词：自动指纹识别系统 指纹分类 连续分布方向图 奇异点检测 POINCARÉ INDEX 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]