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指纹匹配中的关键问题研究
其他题名Study on Key Issues of Fingerprint Matching
郑晓隆
学位类型工学博士
导师王阳生
2008-06-03
学位授予单位中国科学院研究生院
学位授予地点中国科学院自动化研究所
学位专业模式识别与智能系统
关键词指纹分割 方向场 奇异点检测 指纹对齐 细节点打分 指纹匹配 Fingerprint Segmentation Orientation Field Singular Point Detection Fingerprint Alignment Minutia Scoring Fingerprint Match
摘要自动指纹识别技术利用指纹所固有的生理特征进行身份鉴证,其具有广泛的应用前景。由于指纹特征的唯一性和稳定性以及指纹识别系统的可行性,自动指纹识别技术受到了许多研究者的关注。指纹匹配是自动指纹识别中的重要环节,其对识别系统的性能有重要影响,本文以指纹匹配为研究主体,对其中的一些关键问题进行了研究。论文的主要贡献如下: 1) 指纹分割对于提高处理速度和滤除伪细节点以及伪奇异点都有重要意义。本文为能得到更加可靠的奇异点,对指纹分割做了深入的研究,提出了一种基于主动轮廓线的指纹分割方法。首先是建立指纹前景区的描述特征,再采用主动轮廓线来分割特征图,定位前景区边缘,这样对模糊的边缘也可以定位得较好。针对分块的前景区边缘粗糙,本文提出了一种曲线滤波的方法来平滑前景区边缘。实验结果表明通过这种方法可以精确地定位边缘,而且是单像素级的光滑边缘。 2) 在基于灰度梯度的基础上,通过傅立叶域分析,采用方向合成方法,改进了指纹方向场的估计。提出了一种基于指纹方向场和指纹曲率场的奇异点检测方法,通过度量图像的局部方向场的离散程度再结合在方向场的基础上计算得到的曲率来定位指纹的奇异点。依据指纹奇异点,限制指纹细节点搜索范围,当比对两枚指纹时,只比对落在一定范围内的细节点对,这样大大提高了匹配的速度。 3) 提出了一种基于指纹纹线相似性的指纹对齐方法。首先对指纹细节点所关联的细化线进行采样,再从查询指纹和模板指纹中各取一个细节点,从纹线采样中直接估计它们的水平和垂直方向的位移以及旋转角度,并将脊线间的相似度表示为与采样点拟合误差相关的量,最后在一个三维空间内搜索相似度最高的一对细节点做为参考点,实验结果表明,这种方法可以有效地找到参考点用于度量指纹间的相似性。 4) 针对指纹形变提出了一种鲁棒的度量指纹间相似度的方法。首先通过对方向场差建模,利用贝叶斯方法,可以通过方向场差来给出一对指纹图像是否来自同一枚指纹的概率;再通过对指纹细节点打分,找到一些绝对可靠的细节点,加倍弹性界限盒的尺度,越少这种细节点不匹配就从另一个侧面表明指纹越相似。最后结合细节点匹配分数和以上两种相似性度量给出一个综合的匹配分数,实验结果要优于采用单一的匹配分数。
其他摘要Automatic fingerprint recognition technique performs personal identification based on the intrinsic physiological feature of fingerprint and has wide application prospect. Automatic fingerprint recognition technique has received extensive attention from researchers all over the world. Fingerprint matching plays significant role on the performance of recognition system. This thesis focuses on fingerprint matching, in which some key problems are studied deeply. And the main contributions of this thesis are as follows: 1. A segmentation method based on active contour model is proposed. Firstly, descriptors of fingerprint foreground are constructed, then active contour model is performed on the descriptor image, therefore, the foreground border is located automatically. Due to the block effect, the envelope of fingerprint foreground is coarse in the sense of pixel level. A curve filter method as a postprocessing is proposed to smooth the border of foreground. Experimental results show that borders of foreground can be located with single-pixel precision. 2. Base on the gray scale gradient, the estimation of fingerprint orientation filed is improved through direction composition in Fourier domain. A new detection method is proposed by combining the measure of local orientation disorder with the curvature field which calculated from orientation field. According to singular points, the searching range of minutia pairing is bounded, only those minutiae which fall into a certain scope are considered when match two fingerprints, thus, the matching speed can be improved greatly. 3. Proposes a fingerprint alignment method based on local ridge similarity. We firstly sample the thinning ridges which associate with corresponding minutiae. The horizontal and vertical shift are estimated directly from minutiae, while the rotation between two ridges is estimated through curve fitting. Final, the similarity between two ridges is represented by a related measure with fitting error. The minutia pair corresponding to the peak in the three dimension histogram of local ridge similarity is assigned as the reference points. Experimental results show that the proposed method can effectively accomplish fingerprint alignment which provides the basis to measure the similarity between two fingerprints. 4. A robust approach of measuring the similarity between two fingerprints is proposed. Firstly, we model the orientation difference and apply Bayesian rule to obtain a probability which indicates the likelihood weather two fingerprints came from the same finger. Secondly, we select absolute reliable minutiae by minutiae scoring and double the bounding box. Therefore, the less such minutiae failing to match means the more similarity between two fingerprints. And finally, we fuse the two similarity measures with the matching minutia score to give a comprehensive matching score. Experimental results demonstrate that the fused score performs better than the single one.
馆藏号XWLW1261
其他标识符200518014628085
语种中文
文献类型学位论文
条目标识符http://ir.ia.ac.cn/handle/173211/6116
专题毕业生_博士学位论文
推荐引用方式
GB/T 7714
郑晓隆. 指纹匹配中的关键问题研究[D]. 中国科学院自动化研究所. 中国科学院研究生院,2008.
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