摘要： 提出一种基于流场与劳伦级数的指纹奇异点检测算法。运用指纹标量场的梯度信息得到指纹流场，在指纹流场与劳伦多项式之间互相关性的基础上，采用多尺度复数滤波的互相关性能量检测指纹奇异点。在SPD2010指纹数据库上进行实验研究，结果验证该算法能够实现指纹流场中奇异点的旋转不变性检测，检测效果优于SPD2010中的最优算法。
关键词:
指纹检测,
奇异点,
流场,
劳伦级数,
互相关性能量,
旋转不变性
Abstract: A new detection algorithm of fingerprint singular points is proposed in this paper, based on flow field and Laurent series. Fingerprint orientation flow field is obtained, by using the gradient of fingerprint scalar field. Candidate singularities are detected using the cross-correlation energy calculated between fingerprint orientation flow field and complex-valued filters derived from a novel multi-scale Laurent polynomial model, which allows for rotation invariant detection of singular points in general flow fields. The algorithm is tested on SPD2010 database. Results show that the proposed algorithm outperforms the best detecting algorithm by large margin and the detection is invariant to rotational transformations.
Key words:
fingerprint detection,
singular point,
flow field,
Laurent series,
cross-correlation energy,
rotation invariance
中图分类号:
彭可, 刘琴, 刘巍, 李仲阳, 兰浩. 基于流场与劳伦级数的指纹奇异点检测算法[J]. 计算机工程, 2013, 39(6): 227-230,235.
BANG Ge, LIU Qin, LIU Wei, LI Zhong-Yang, LAN Gao. Fingerprint Singular Points Detection Algorithm Based on Flow Field and Laurent Series[J]. Computer Engineering, 2013, 39(6): 227-230,235.