计算机工程与应用 ›› 2012, Vol. 48 ›› Issue (32): 203-207.

• 图形、图像、模式识别 • 上一篇    下一篇

指纹奇异点精确定位新方法

张祖泷1,杨永明1,韩凤玲2,林坤明1   

  1. 1.重庆大学 输配电装备及系统安全与新技术国家重点实验室,重庆 400044
    2.澳大利亚皇家墨尔本理工大学 计算机科学与信息学院,澳大利亚 墨尔本 3001
  • 出版日期:2012-11-11 发布日期:2012-11-20

New method of singular points accurate location for fingerprint

ZHANG Zulong1, YANG Yongming1, HAN Fengling2, LIN Kunming1   

  1. 1.State Key Lab of Power Transmission Equipment & System Security and New Technology, Chongqing University, Chongqing 400044, China
    2.School of Computer Science and Information Technology, Royal Melbourne Institure of Technology, Melbourne 3001, Australia
  • Online:2012-11-11 Published:2012-11-20

摘要: 针对指纹图像奇异点快速精确定位的难题,提出一种简单实用算法。对指纹图像预处理,计算方向场并归域化,接着选出奇异点候选区,并以Poincare Index(PI)算法从中提取奇异点候选点集。对候选奇异点集去伪并精确定位。采用FVC2004指纹库进行实验验证,结果与PI算法对比,该算法鲁棒性更好,定位更精确,漏检率和误检率分别降低5.86%、6.8%,平均速度提高了3.71~9.38倍,基本满足高精度高速度的指纹奇异点定位要求。

关键词: 指纹图像, 方向场, 奇异点, 归域化

Abstract: An effective new algorithm is proposed for improving the stability and reliability of Singular Points(SPs) location. It preprocesses the gray level fingerprint images, calculates the orientation field, and divides the orientation field into several homogeneous zones and selects candidate small areas. Candidate singular points are chosen out by Poincare Index Algorithm(PIA) and spurious singular points are further removed. The real singular points are precisely located. FVC2004 is used for algorithm testing and the results show that singular points location of the method is more precise, and the False Detecting Ratio(FDR)and the Missed Detecting Ratio(MDR) decrease 5.86% and 6.8% respectively, at the same time, the speed of the algorithm is 3.71~9.38 times faster than PIA, which basicallies satisfies the requirement of SPs accurate detection and location in fingerprint images.

Key words: fingerprint image, orientation field, singular points, homogeneous-zones-divide