地统计关联特征与多子集匹配的缺失指纹识别算法  

Missing fingerprint identification based on linked features of geostatistics and subset matches

作　　者：陈云志[1] 

机构地区：[1]杭州职业技术学院,杭州310018

出　　处：《计算机工程与应用》2014年第10期165-170,共6页Computer Engineering and Applications

基　　金：浙江省科技厅高技能人才培养项目(No.2011R30057)

摘　　要：针对主流指纹识别算法对缺失指纹图像识别率非常低的问题,提出了一种地统计关联特征与多子集匹配的算法(GS-MS)。首先对指纹图像进行Gabor滤波增强以及二值化、细化预处理,然后将图像均匀划分为N个子集,分别提取各子集的地统计学关联特征与分叉点、端点等细节特征点,最后以待识别指纹图像子集为基准,与指纹库子集进行匹配识别。采用完整与缺失两种指纹数据集进行测试,GS-MS算法均取得了较优的识别精度,而且没有大幅度增加运行时间。Most fingerprint identification algorithm has low accuracy for incomplete image, a novel miss fingerprint identification based on linked features of geostatistics and subset matching is proposed in this paper. Image preprocessing is performed by Gabor filter, binary conversion and thinning. The image is partitioned into several sub-images without over-lapped image. The features of each sub-image are extracted such as the linked features of geostatistics, fingerprint minutiaes of fork point and endpoint. The performance of algorithm is test by simulation experiments. The result shows that the proposed method has achieved higher identification accuracy in missing images and has not increased consuming time.

关 键 词：指纹识别 缺失图像 关联特征 地统计学 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]