Computer Engineering and Applications ›› 2008, Vol. 44 ›› Issue (16): 188-190.

• 图形、图像、模式识别 • Previous Articles     Next Articles

Fingerprint separation based on morphological component analysis

GENG Rui-min1,LIAN Qiu-sheng2,SUN Ma-qiu3   

  1. 1.Department of Information Science and Engineering,Yanshan University,Qinhuangdao,Hebei 066004,China
    2.Department of Information Science and Engineering,Yanshan University,Qinhuangdao,Hebei 066004,China
    3.Department of Electronic Information Engineering,Tianjin University,Tianjin 300072,China
  • Received:2007-09-07 Revised:2007-12-10 Online:2008-06-01 Published:2008-06-01
  • Contact: GENG Rui-min

基于形态学成分分析的指纹分离

耿瑞敏1,练秋生2,孙马秋3   

  1. 1.燕山大学 信息科学与工程学院,河北 秦皇岛 066004
    2.燕山大学 信息科学与工程学院,河北 秦皇岛 066004
    3.天津大学 电子信息工程学院,天津 300072
  • 通讯作者: 耿瑞敏

Abstract: Based on the characteristic of the fingerprint,after making some changes on the morphological component analysis and combining the MCA with the harris corner detector,it puts forward a fingerprint separation algorithm.This algorithm is based on the basis pursuit denosing algorithm.Firstly,it uses two same dictionaries to represent sparsely the overlapping fingerprint image or the mixture of the finger and the texture background,then shrinks the sparse coefficients with the soft thresh.After this,minimizes the harris-like operator of the two separating texture images respectively using gradient descending algorithm,to make the coners of the two images minimized.Lastly,it implements total variation regulation on one of the two separating images to achieve separation.Experimentation results indicate that this algorithm can realize fingerprint separation.

摘要: 针对指纹图像的特点,对形态学成分分析进行改造,将其与角点检测器相结合,提出了一种指纹分离算法。算法基于基追踪去噪算法,首先对重叠指纹图像或者指纹与背景纹理重叠的图像采用两个相同的纹理词典进行稀疏表示,对稀疏系数软门限收缩之后进行反变换得到两幅纹理图像,然后使用梯度下降法最小化分离出来的两幅纹理图像的harris-like算子,使得两幅图像的角点均最少,再对其中一幅图像进行全方差调整,从而达到分离的目的。实验结果表明此方法能够实现指纹分离。