计算机与现代化 ›› 2014, Vol. 0 ›› Issue (1): 81-85.

• 算法设计与分析 • 上一篇    下一篇

基于方向图和Gabor滤波的指纹预处理算法

  

  1. 1.西安电子科技大学物理与光电工程学院,陕西西安710071;2.西安电子科技大学通信工程学院,陕西西安710071
  • 收稿日期:2013-08-26 出版日期:2014-01-20 发布日期:2014-02-10
  • 作者简介: 付玉虎(1986-),男,山东枣庄人,西安电子科技大学物理与光电工程学院硕士研究生,研究方向:自动指纹识别技术; 杜月荣(1988-),男,硕士研究生,研究方向:数字图像处理; 李哲哲(1987-),女,西安电子科技大学通信工程学院硕士研究生,研究方向:无线通信,算法。

 Preprocessing Algorithm for Fingerprint Image Based on Orientation and Gabor Filter

  1. 1. School of Physics Optoelectronic Engineering, Xidian University, Xi’an 710071, China;

     2. School of Telecommunications Engineering, Xidian University, Xi’an 710071, China
  • Received:2013-08-26 Online:2014-01-20 Published:2014-02-10

摘要: 指纹图像在预处理过程中往往受多方面因素制约,有时无法满足指纹识别系统的要求。本文在传统指纹预处理算法基础上,给出一种有效的指纹预处理改进算法。首先,采用分块方差梯度分割算法分离指纹图像和背景区;再根据指纹特征,用方向图和均值滤波器进行图像增强,并用简化的Gabor滤波器,改进滤波模板滤除边缘模糊效应。二值化、细化并删除伪特征点后,提取出指纹脊线骨架并获得指纹特征点。实验表明,该预处理算法对不同质量的指纹图像均具有较好效果,算法灵活高效、易于实现、精确度高,达到了指纹识别系统的要求。

关键词: 指纹识别, 块梯度方差, 伪特征点删除, 均值滤波, 二值化

Abstract: The fingerprint image in preprocessing is often affected by many factors, but sometimes can not meet the requirements of fingerprint identification system. In this article, an effective fingerprint preprocessing algorithm is presented based on the traditional methods for preprocessing. Firstly, a method based on block gradient variance is implemented to achieve the separation of the fingerprint image and the background area. Secondly, according to the fingerprint feature, we use orientation map and mean filter to enhance the image. And using simplified Gabor filter improves the filtering template to filter edge blur effect. After binarization, thinning and eliminating pseudo minutiae, we get the fingerprint image skeletonization and extract the fingerprint feature points. Experiments show that the preprocessing algorithm is applicable to images of different qualities and levels. It is flexible, efficient, easy, and accurate, meets the requirement of fingerprint identification system.

Key words: fingerprint identification, block gradient variance, eliminating pseudo minutiae, mean filtering, binarization