Abstract: Authors introduce a new feature called Orientation Abundance Degree（OAD） based on fingerprint’s orientation segmentation，and propose an effective method for detection of fingerprint’s SP by using OAD.In this method，fingerprint’s orientation is partitioned into a series of non-overnapping homogeneous areas firstly；then SPs are rapidly localized through edges detection of homogeneous areas and end-points extraction of edges；finally，the types of SPs are distinguished according to the Poincare Index value.Compared with the Poincare Index method（PI），experiments on FVC2002 show that：for the performance of accuracy，the False Detecting Ratio（FDR） of our method is much lower than PI’s FDR，and the Missed Detecting Ratio（MDR） is a little higher than PI’s MDR；for the performance of practicality，our method owns obvious superiority，the speed of our method is 14.2 times faster than PI.

Key words: fingerprint, singular point, orientation field

摘要： 在指纹方向场分割的基础上提出了一种称之为方向丰富度的特征，并据此形成了一种有效的指纹奇异点提取方法。该方法首先将指纹方向场分割为一系列互不重叠的同质区域；然后通过同质区域边缘检测及边缘端点提取实现了奇异点快速定位；最后依据已定位点的poincare index值确定奇异点类型。与目前占据绝对主流的poincare index方法在FVC2002指纹库上的对比实验表明：在准确性方面，两者各有优、缺点，该文方法的误检率明显低于后者，漏检率略高于后者；在简单实用性方面，该文算法的平均提取速度是后者的14.2倍，具有明显优势。

关键词: 指纹, 奇异点, 方向场