CAJ | 학술논문

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。
침대주류지문식별산법대결실지문도상식별솔비상저적문제，제출료일충지통계관련특정여다자집필배적산법（GS-MS）。수선대지문도상진행Gabor려파증강이급이치화、세화예처리，연후장도상균균화분위N개자집，분별제취각자집적지통계학관련특정여분차점、단점등세절특정점，최후이대식별지문도상자집위기준，여지문고자집진행필배식별。채용완정여결실량충지문수거집진행측시，GS-MS산법균취득료교우적식별정도，이차몰유대폭도증가운행시간。
Most fingerprint identification algorithm has low accuracy for incomplete image, a novel miss fingerprint iden-tification 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 pro-posed method has achieved higher identification accuracy in missing images and has not increased consuming time.