指纹图像质量的自动评定  

Automatic quality assessment of fingerprint image

作　　者：杨永明[1] 张祖泷[1] 韩凤玲[2] 林坤明[1] 孙豪 

机构地区：[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 [3]南方电网超高压输电公司安宁局,云南6503OO

出　　处：《重庆大学学报（自然科学版）》2012年第11期92-98,共7页Journal of Chongqing University

基　　金：国家重点实验室访问学者基金资助项目(2007DA10512709403);中央高校基本科研业务费资助项目(CDJXS11150014)

摘　　要：针对指纹图像质量差而导致指纹识别系统识别成功率低下的问题,提出一种基于多影响因子的指纹图像质量自动评定方法。以原始指纹图像的局部纹理、全局纹理、可利用面积大小和干湿状况作为影响因子,先以梯度相关性计算局部纹理质量分数,再以分块思想分别计算出后三者的质量分数。然后,以不同的影响权值将上述4个影响因子联系起来,综合评定指纹质量。最后调节部分影响因子的影响作用,修正综合评定结果。采用FVC2004DB2_B中图像进行算法验证,实验结果表明:能合理有效地将指纹图像质量评定为5个等级,而且正确率可达到97.5%,能有效提高指纹识别系统的识别成功率。Based on multiple influencing factors,a new method of automatic fingerprint image quality evaluation is proposed for improving the success rate of automation fingerprint identification system（AFIS）.At first,the original image＇s local texture,global texture,available size and dry or wet condition are regarded as quality impact factors,local texture quality score is calculated by local gradient correlation,and then the last three factors＇ quality scores are obtained by block computation thought.Then,with different influence weights,the above four impact factors are linked together to assess image quality synthetically.Finally,effect of partial impact factor is adjusted to correct the final quality score.FVC2004DB2_B is used for algorithm testing.The results suggest that this method can reasonably classify fingerprint image into 5 grades and the precision can achieve 97.5%,and that shows the method is helpful to success rate of AFIS.

关 键 词：指纹识别系统 图像处理 图像质量 影响因子 指纹纹理 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]