用于生物特征数据分类的SVM算法改进
发布时间：2023-05-05 23:43
随着计算机科学和互联网技术的飞速发展,生物识别技术在我们的社会生活中得到了广泛的应用,如指纹识别,人脸识别等。由于人脸识别具有强制性,接触性等,并且,作为一种生物识别技术,人脸识别方法很快成为一个重要的研究领域。人脸识别是模式识别中的热门话题。因为其便利性,人脸识别被广泛的应用于有较高安全要求的认证,检测和调查中。人脸识别算法从最初的简单条件下的识别发展到多因素复杂条件下的识别。复杂条件下的人脸识别要考虑光线,面部旋转,面部遮挡,噪声污染,肤色和种族因素等多种因素。因此,复杂条件下的人脸识别仍然是人脸识别领域的难题。本文研究了生物特征数据分类的问题。使用支持向量机算法对生物特征数据分类己经被广泛使用,但识别需要很长时间。为了减少算法运行时间,通常采用降维。在将数据导入分类算法之前,先对数据做降维的预处理。过去,许多研究人员已经提出了使用降维技术对生物特征数据进行分类的各种技术,并且大多数技术已用于人脸图像数据分类。准确率是衡量模型性能最重要的指标。对几种生物特征数据降维处理后进行分类,然后比较分类时间。但是,这样处理很复杂,所以,这种研究方法很少用。因此,在本文中对使用支持向量机算法识...
【文章页数】：61 页
【学位级别】：硕士
【文章目录】：
摘要
ABSTRACT
Chapter 1 Introduction
1.1 The importance and origin of research problems
1.2 Research background and significance
1.2.1 Research background
1.2.2 Significance
1.3 Research status at home and abroad
1.3.1 Domestic Research status
1.3.2 Foreign research status
1.4 Thesis Organization
Chapter 2 Literary review and related research
2.1 Biometric
2.1.1 Definition and type of biometric
2.1.2 Biometric Applications
2.1.3 Benefits of Biometric Implementation
2.2 Support Vector Machine (SVM)
2.2.1 Applications of SVM
2.2.2 Linear Support Vector Machine
2.2.3 Nonlinear classification
2.3 Linear Discriminant Analysis (LDA)
Chapter 3 The method of the research
3.1 Research Framework
3.2 Algorithm Design
3.2.1 Algorithm design Support Vector Machine for Biometric Data Classification
3.2.2 Performance testing modeling of the support vector machine algorithm for biometric data classification
3.2.3 Research tools
Chapter 4 Testing and discussion
4.1 Test data
4.1.1 Face-Recognition
4.1.2 Fingerprint-classification
4.1.3 Signature-Verification
4.2 Performance testing Improved support vector machine algorithm
4.2.1 Effects of how to use SVM
4.2.2 Effects of Bio-SVM on physical Biomedical Data
4.2.3 Effects of Bio-SVM on Behavioral Biometric Data
4.3 Comparison of experimental results Biometric Image classification with Algorithms Various
4.4 Discuss the results
4.5 Summary and Future Work
Chapter 5 Conclusions
Bibliography
Acknowledgement
Biography
本文编号：3808597
【文章页数】：61 页
【学位级别】：硕士
【文章目录】：
摘要
ABSTRACT
Chapter 1 Introduction
1.1 The importance and origin of research problems
1.2 Research background and significance
1.2.1 Research background
1.2.2 Significance
1.3 Research status at home and abroad
1.3.1 Domestic Research status
1.3.2 Foreign research status
1.4 Thesis Organization
Chapter 2 Literary review and related research
2.1 Biometric
2.1.1 Definition and type of biometric
2.1.2 Biometric Applications
2.1.3 Benefits of Biometric Implementation
2.2 Support Vector Machine (SVM)
2.2.1 Applications of SVM
2.2.2 Linear Support Vector Machine
2.2.3 Nonlinear classification
2.3 Linear Discriminant Analysis (LDA)
Chapter 3 The method of the research
3.1 Research Framework
3.2 Algorithm Design
3.2.1 Algorithm design Support Vector Machine for Biometric Data Classification
3.2.2 Performance testing modeling of the support vector machine algorithm for biometric data classification
3.2.3 Research tools
Chapter 4 Testing and discussion
4.1 Test data
4.1.1 Face-Recognition
4.1.2 Fingerprint-classification
4.1.3 Signature-Verification
4.2 Performance testing Improved support vector machine algorithm
4.2.1 Effects of how to use SVM
4.2.2 Effects of Bio-SVM on physical Biomedical Data
4.2.3 Effects of Bio-SVM on Behavioral Biometric Data
4.3 Comparison of experimental results Biometric Image classification with Algorithms Various
4.4 Discuss the results
4.5 Summary and Future Work
Chapter 5 Conclusions
Bibliography
Acknowledgement
Biography
本文编号：3808597
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