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指纹图像预处理及其在嵌入式系统中的应用
Alternative TitleNGERPRINT IMAGE PREPROCESSING AND ITS APPLIATION IN EMBEDDED SYSTEMS
王森
Subtype工学硕士
Thesis Advisor王阳生
2003-05-01
Degree Grantor中国科学院研究生院
Place of Conferral中国科学院自动化研究所
Degree Discipline模式识别与智能系统
Keyword生物识别 自动指纹识别系统 图象处理 指纹预处理 嵌入式系统 Biometrics Automatic Fingerprint Identification System Image Processing Fingerprint Preprocessing Embedded Systems
Abstract随着科技的日新月异,身份鉴别技术日益显示出重要性和必要性。生物特 征用来鉴别身份使得鉴别系统在性能、安全和方便方面得到很大的提高。而指 纹识别系统作为历史最悠久的生物特征识别方法得到最广泛的应用。本文作者 在攻读硕士学位期间主要从事自动指纹识别系统中指纹图象预处理方面核心算 法的研究。本文主要贡献如下: (1)对目前自动指纹身份识别系统中指纹图象预处理方面的研究现状进行了 比较全面介绍,对目前指纹研究的主流方法做了比较全面的综述。 (2)在指纹分类方面,提出了一种新的指纹分类的方法,通过只提取中心点 及其周围纹路的方向信息作为特征,然后选取K均值和3近邻分类器来 对指纹图象进行分类。该方法比用奇异点进行分类的方法在精度上有很 大的提高。 (3)在指纹背景分割方面,提出了一种新的指纹图象分割方法,分别在空域 和频域中定义了两个新特征:对比度(Contrast)和主能量比(Main Energy Ratio),并用RBF神经网络训练分类和进行分割。通过新的分割方法可以 很好区分出指纹图象中纹路的前景区域和模糊区域。由于在模糊区域很 容易提取出许多虚假细节,因此,成功分割出模糊区域就降低了特征提 取中虚假细节的数目,提高了特征提取的精度,从而提高了自动指纹识 别系统的整体性能。 (4)在指纹图象增强滤波方面,提出了一种新的指纹纹路增强方法,把纹路 分为正常区域和奇异区域。由于两个区域中指纹纹路宽度和方向的变化 差别都比较大,所以我们分别设计滤波器对不同区域进行增强。此外还 应用了纹路宽度估计方法,使得滤波器参数求取更加准确,从而得到更 好的增强滤波效果。 (5)介绍了指纹图象预处理技术在嵌入式指纹识别系统和指纹锁核心模块中 的应用。
Other AbstractWith development of technology, the accurate personal identification becomes more and more important and necessary. The use of biometrics in personal identification highly improves the performance, security and convenience of the identification system. As the oldest mode of biometrics, fingerprint identification system is the most prevalent in use today. This thesis focuses on algorithm of feature extraction related to Automatic Fingerprint Identification Systems (AFIS), and the main contributions are as follows: (1) A comprehensive preview is presented on fingerprint image preprocessing on the state of the core algorithm related to AFIS. (2) We present a novel fingerprint classification algorithm that is based directional fields. Then we extract features that we define from fingerprint images. We also use k-mean and 3 nearest neighbor to classify features and distinguish the fingerprint. This algorithm improves accuracy more highly than the algorithm which uses the singular points. (3) A new fingerprint image segmentation algorithm is proposed. We define two features: contrast and main energy ration in the special domain and frequency domain respectively. Then we use RBF neural network to perform training, classification and segmentation. Because by the use of this new algorithm of segmentation we can reduce the number of false minutiae extracted in the blurred area and improve the accuracy of feature extraction and the whole performance of AFIS. (4) We present a new algorithm of fingerprint enhancement. Because there are many differences in the normal ridge area and the singular point area, we must classify these two areas, design filters and enhance them respectively. Moreover, because the method of ridge width estimation is used, we get the better result of enhancement. (5) We introduce an embedded fingerprint identification system and the application of fingerprint image preprocessing in fingerprint lock recognition module.
shelfnumXWLW699
Other Identifier699
Language中文
Document Type学位论文
Identifierhttp://ir.ia.ac.cn/handle/173211/6812
Collection毕业生_硕士学位论文
Recommended Citation
GB/T 7714
王森. 指纹图像预处理及其在嵌入式系统中的应用[D]. 中国科学院自动化研究所. 中国科学院研究生院,2003.
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