自动指纹识别系统关键技术研究
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摘要
作为现代身份鉴别的重要工具,生物识别技术正前所未有地引起人们的关注。指纹识别是最具代表性的生物识别技术之一,不仅已在司法领域取得巨大成功,而且开始涉足广阔的民用领域,在现代社会中正不断发挥其重要作用。
自动指纹识别系统涉及图像处理、模式识别、计算机和传感器等多种技术,是随着人们对指纹识别需求的不断增加而产生的,对它的研究可以追溯到20世纪60年代初期。经过近半个世纪的发展,自动指纹识别系统在各方面性能上都有了长足的进步。但是,由于指纹识别所特有的复杂性和不确定性,自动指纹识别系统仍面临着不少问题有待解决和完善。
指纹识别算法是自动指纹识别系统的核心和关键,该文以指纹识别算法为重点进行研究,并在算法研究的基础上实际构建了一个自动指纹识别系统,主要完成了如下工作:
1.该文研究了指纹图像质量评价,分析了现有方法的不足,并提出一种新的指纹图像质量评价算法。该算法利用模糊推理系统(FIS)的模糊处理能力对指纹图像的多种特征进行综合分析,并利用支持向量机(SVM)的小样本学习、全局最优和泛化能力强等特点实现比较可靠的图像分割,在此基础上最终完成指纹图像的总体质量评价。实验结果表明,该算法能够合理区分不同质量的指纹图像,有助于改善自动指纹识别系统的整体性能。
2.该文研究了指纹图像增强,对指纹图像增强的研究状况作了概括介绍,指出当前最具代表性的Gabor滤波方法所固有的缺陷,并提出一种新的指纹图像增强算法,首次将目前正引起关注的Log-Gabor滤波器用于指纹图像增强。该算法利用Log-Gabor滤波器独特的频率响应特性,有效克服了传统Gabor滤波器的局限性,首先根据指纹的纹理信息构造出Log-Gabor滤波器组,然后通过合理的频域滤波实现指纹图像增强。实验结果表明,该算法能显著改善原始指纹图像的质量,有助于提高自动指纹识别系统的准确性和鲁棒性。
3.该文研究了指纹匹配,对现有的指纹匹配算法作了概括介绍和比较,在此基础上提出一种新的指纹匹配算法。该算法首先利用脊线信息快速确定满足局部匹配要求的细节点对,在此基础上进一步通过全局坐标变换完成细节点的全局配准,并采用仿射变换模型通过最小二乘估计对配准参数进行优化,然后在配准的基础上分别进行细节点匹配和方向场匹配,最后对两种匹配分值进行融合,以取得较合理的匹配结果。实验结果表明,该算法不仅能保证指纹识别的准确性,而且还具有较高的实时性。
4.该文设计和实现了一个具有自主知识产权的嵌入式指纹识别系统,对嵌入式系统的硬件平台和软件系统进行了较全面的研究和设计,并在嵌入式系统上移植和实现了指纹识别算法。系统的硬件体系结构已获国家专利授权,相应的软件系统则通过国家软件产品登记测试。验证样机所达到的技术指标表明,该系统具有较高的实际应用价值。
该文系统而深入地研究了自动指纹识别系统的理论和技术,在指纹图像质量评价、指纹图像增强和指纹匹配等核心算法上均作了创新性的工作,提出有效的新方法,并最终设计和实现了一个具有自主知识产权的嵌入式指纹识别系统。该文的研究工作为进一步完善自动指纹识别系统提供了重要的理论依据和技术基础,对于促进自动指纹识别技术的发展和应用有着积极的意义。
As a significant approach to personal identification, biometrics is attracting unprecedented attention. Fingerprint identification is one of the most representative technologies of biometrics and has achieved great success both in police and civil applications.
Automatic fingerprint identification system (AFIS) involves the technologies of image processing, pattern recognition, computer and sensor. It is developed with the increasing demand for fingerprint identification and the origins of the research can be traced back to the early 1960s. With a half century of development, the performance of AFIS has been greatly improved. However, due to the complexity and uncertainty of fingerprint identification, there are still many problems to be resolved for further improvement of AFIS.
The dissertation primarily investigated the fingerprint identification algorithm which is one of the most key technologies of AFIS, and further constructed a practical system based on the research of algorithm. The main contributions of the dissertation are as following:
1. The dissertation investigated fingerprint image quality evaluation and proposed a new evaluation method considering the limitations of the existed methods. The proposed method makes comprehensive analysis on various features of a fingerprint image by utilizing the fuzzy inference system (FIS), and carries out accurate image segmentation by utilizing the support vector machine (SVM). Based on this, the global quality of fingerprint image is finally evaluated. Experimental results show that the proposed method has the ability to distinguish between fingerprint images with various qualities and may contribute to promote the performance of AFIS.
2. The dissertation made a survey on fingerprint image enhancement and proposed a novel enhancement algorithm which adopts Log-Gabor filters to enhance fingerprint images for the first time. The proposed algorithm effectively overcomes the drawbacks result from the limitations of traditional Gabor filters in virtue of the unique frequency response characteristic of Log-Gabor filters. In this algorithm, a bank of Log-Gabor filters is constructed according to the texture features of fingerprint image, and the image is enhanced by frequency filtering. Experimental results show that the proposed algorithm can effectively improve the quality of fingerprint images and help to ensure the accuracy and robustness of AFIS.
3. The dissertation investigated fingerprint matching and presented a new matching method based on the analysis and comparison of the existed methods. This method firstly searches the minutiae pairs which satisfied the requirement of local matching by utilizing the ridge information. Then, the minutiae sets are aligned globally through coordinate transform, and the alignment parameters are optimized by using affine transform and least square method. Finally, minutiae matching and directional field matching are respectively achieved based on the minutiae alignment, and the two matching scores are fused into a single to obtain a more reasonable result. Experimental results show that this method contributes to ensure the accuracy of fingerprint identification as well as possesses the real-time performance.
4. The dissertation designed and realized an embedded fingerprint identification system which owns independent intellectual property. In this work, both the hardware platform and the software system are investigated and designed, and the algorithm of fingerprint identification is also successfully transplanted into the embedded system. The hardware structure has been awarded the Chinese Patent and the corresponding software system already passed the software product register test of Chongqing software test center. The achieved technical performance level shows that this system is of considerable practical value.
The dissertation systemically and deeply investigated the theory and methods of AFIS, brought forth new ideas on fingerprint image quality evaluation, fingerprint image enhancement and fingerprint matching, and eventually realized an embedded fingerprint identification system with independent intellectual property. This study may provide theoretical and technical support for further developing the AFIS with higher performance. It is of active significance to promote the development and application of automatic fingerprint identification technology.
自动指纹识别系统涉及图像处理、模式识别、计算机和传感器等多种技术,是随着人们对指纹识别需求的不断增加而产生的,对它的研究可以追溯到20世纪60年代初期。经过近半个世纪的发展,自动指纹识别系统在各方面性能上都有了长足的进步。但是,由于指纹识别所特有的复杂性和不确定性,自动指纹识别系统仍面临着不少问题有待解决和完善。
指纹识别算法是自动指纹识别系统的核心和关键,该文以指纹识别算法为重点进行研究,并在算法研究的基础上实际构建了一个自动指纹识别系统,主要完成了如下工作:
1.该文研究了指纹图像质量评价,分析了现有方法的不足,并提出一种新的指纹图像质量评价算法。该算法利用模糊推理系统(FIS)的模糊处理能力对指纹图像的多种特征进行综合分析,并利用支持向量机(SVM)的小样本学习、全局最优和泛化能力强等特点实现比较可靠的图像分割,在此基础上最终完成指纹图像的总体质量评价。实验结果表明,该算法能够合理区分不同质量的指纹图像,有助于改善自动指纹识别系统的整体性能。
2.该文研究了指纹图像增强,对指纹图像增强的研究状况作了概括介绍,指出当前最具代表性的Gabor滤波方法所固有的缺陷,并提出一种新的指纹图像增强算法,首次将目前正引起关注的Log-Gabor滤波器用于指纹图像增强。该算法利用Log-Gabor滤波器独特的频率响应特性,有效克服了传统Gabor滤波器的局限性,首先根据指纹的纹理信息构造出Log-Gabor滤波器组,然后通过合理的频域滤波实现指纹图像增强。实验结果表明,该算法能显著改善原始指纹图像的质量,有助于提高自动指纹识别系统的准确性和鲁棒性。
3.该文研究了指纹匹配,对现有的指纹匹配算法作了概括介绍和比较,在此基础上提出一种新的指纹匹配算法。该算法首先利用脊线信息快速确定满足局部匹配要求的细节点对,在此基础上进一步通过全局坐标变换完成细节点的全局配准,并采用仿射变换模型通过最小二乘估计对配准参数进行优化,然后在配准的基础上分别进行细节点匹配和方向场匹配,最后对两种匹配分值进行融合,以取得较合理的匹配结果。实验结果表明,该算法不仅能保证指纹识别的准确性,而且还具有较高的实时性。
4.该文设计和实现了一个具有自主知识产权的嵌入式指纹识别系统,对嵌入式系统的硬件平台和软件系统进行了较全面的研究和设计,并在嵌入式系统上移植和实现了指纹识别算法。系统的硬件体系结构已获国家专利授权,相应的软件系统则通过国家软件产品登记测试。验证样机所达到的技术指标表明,该系统具有较高的实际应用价值。
该文系统而深入地研究了自动指纹识别系统的理论和技术,在指纹图像质量评价、指纹图像增强和指纹匹配等核心算法上均作了创新性的工作,提出有效的新方法,并最终设计和实现了一个具有自主知识产权的嵌入式指纹识别系统。该文的研究工作为进一步完善自动指纹识别系统提供了重要的理论依据和技术基础,对于促进自动指纹识别技术的发展和应用有着积极的意义。
As a significant approach to personal identification, biometrics is attracting unprecedented attention. Fingerprint identification is one of the most representative technologies of biometrics and has achieved great success both in police and civil applications.
Automatic fingerprint identification system (AFIS) involves the technologies of image processing, pattern recognition, computer and sensor. It is developed with the increasing demand for fingerprint identification and the origins of the research can be traced back to the early 1960s. With a half century of development, the performance of AFIS has been greatly improved. However, due to the complexity and uncertainty of fingerprint identification, there are still many problems to be resolved for further improvement of AFIS.
The dissertation primarily investigated the fingerprint identification algorithm which is one of the most key technologies of AFIS, and further constructed a practical system based on the research of algorithm. The main contributions of the dissertation are as following:
1. The dissertation investigated fingerprint image quality evaluation and proposed a new evaluation method considering the limitations of the existed methods. The proposed method makes comprehensive analysis on various features of a fingerprint image by utilizing the fuzzy inference system (FIS), and carries out accurate image segmentation by utilizing the support vector machine (SVM). Based on this, the global quality of fingerprint image is finally evaluated. Experimental results show that the proposed method has the ability to distinguish between fingerprint images with various qualities and may contribute to promote the performance of AFIS.
2. The dissertation made a survey on fingerprint image enhancement and proposed a novel enhancement algorithm which adopts Log-Gabor filters to enhance fingerprint images for the first time. The proposed algorithm effectively overcomes the drawbacks result from the limitations of traditional Gabor filters in virtue of the unique frequency response characteristic of Log-Gabor filters. In this algorithm, a bank of Log-Gabor filters is constructed according to the texture features of fingerprint image, and the image is enhanced by frequency filtering. Experimental results show that the proposed algorithm can effectively improve the quality of fingerprint images and help to ensure the accuracy and robustness of AFIS.
3. The dissertation investigated fingerprint matching and presented a new matching method based on the analysis and comparison of the existed methods. This method firstly searches the minutiae pairs which satisfied the requirement of local matching by utilizing the ridge information. Then, the minutiae sets are aligned globally through coordinate transform, and the alignment parameters are optimized by using affine transform and least square method. Finally, minutiae matching and directional field matching are respectively achieved based on the minutiae alignment, and the two matching scores are fused into a single to obtain a more reasonable result. Experimental results show that this method contributes to ensure the accuracy of fingerprint identification as well as possesses the real-time performance.
4. The dissertation designed and realized an embedded fingerprint identification system which owns independent intellectual property. In this work, both the hardware platform and the software system are investigated and designed, and the algorithm of fingerprint identification is also successfully transplanted into the embedded system. The hardware structure has been awarded the Chinese Patent and the corresponding software system already passed the software product register test of Chongqing software test center. The achieved technical performance level shows that this system is of considerable practical value.
The dissertation systemically and deeply investigated the theory and methods of AFIS, brought forth new ideas on fingerprint image quality evaluation, fingerprint image enhancement and fingerprint matching, and eventually realized an embedded fingerprint identification system with independent intellectual property. This study may provide theoretical and technical support for further developing the AFIS with higher performance. It is of active significance to promote the development and application of automatic fingerprint identification technology.
引文
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