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  • 音像TIRE PATTERN IMAGE RETRIEVAL轮胎花纹图像检索刘颖
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    • 作者: 刘颖著 | 刘颖编 | 刘颖译 | 刘颖绘
    • 出版社: 科学出版社
    • 出版时间:2018-12-01
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    • 作者: 刘颖著| 刘颖编| 刘颖译| 刘颖绘
    • 出版社:科学出版社
    • 出版时间:2018-12-01
    • 版次:1
    • 印次:1
    • 字数:150000
    • 页数:128
    • ISBN:9787030593528
    • 版权提供:科学出版社
    • 作者:刘颖
    • 著:刘颖
    • 装帧:平装
    • 印次:1
    • 定价:98.00
    • ISBN:9787030593528
    • 出版社:科学出版社
    • 开本:暂无
    • 印刷时间:暂无
    • 语种:暂无
    • 出版时间:2018-12-01
    • 页数:128
    • 外部编号:1201811470
    • 版次:1
    • 成品尺寸:暂无

    Preface
    List of Abbreviations
    Chapter 1 Introduction
    1.1 Background
    1.2 Contribution of This Book
    1.3 Organization of This Book
    References
    Chapter 2 A Survey of Image Retrieval Techniques for Tire Pattern Database
    2.1 Introduction
    2.2 Tire Pattern Database and Performance EvaluationMethods
    2.2.1 Tire pattern image databases
    2.2.2 Performance evaluation
    . Tire Pattern Retrieval
    ..1 Tire tread pattern retrieval
    ..2 Tire surface wear feature extraction
    .. Video tire pattern retrieval
    ..4 Tire indentation mariae retrieval
    ..5 Summary
    2.4 Discussion about Future Research Directions
    2.4.1 Standard test dataset and performance evaluation
    2.4.2 Matching between tire indentation mark and tire tread pattern
    2.5 Conclusions
    References
    Chapter 3 A Modified Tamura Feature for Tire Pattern Image Description
    3.1 Introduction of Tamura Feature
    3.2 Modification of Tamura Texture Feature
    3.2.1 Tamura texture feature
    3.2.2 Modification
    3.3 Experimental Results
    3.4 Conclusions
    References
    Chapter 4 H-SIFT: SIFT from High-Frequency Information of Tire Pattern Images
    4.1 Introduction of SIFT Feature
    4.2 Review of SIFT Feature
    4.2.1 Scale space and relevant concepts
    4.2.2 The model of Gaussian pyramid and difference of Gaussian pyramid
    4.. The establishment of the key points
    4.2.4 The key points matching
    4.3 Description of the Proposed Method H-SIFT
    4.4 Experimental Results
    4.5 Conclusions
    References
    Chapter 5 Study on Rotation-Invariant Texture Feature Extraction for Tire Pattern Retrieval
    5.1 Introduction
    5.2 Radon-DTCWT Algorithm
    5.2.1 Radon transform
    5.2.2 Translation sensitivity of ridgelet transform
    5.. The new Radon-DTCWT algorithm
    5.3 Curvelet Energy Distribution Algorithm
    5.3.1 Curvelet transform of tire pattern image
    5.3.2 Direction characteristics of tire pattern images
    5.3.3 Implementation of curvelet energy distribution algorithm
    5.4 Experiment Results
    5.5 Conclusions
    References
    Chapter 6 HOG-TT: A Robust HOG-Based Texture Feature Extraction Method Making Use of Texture Tendency in Tread Pattern Images
    6.1 Introduction
    6.2 Description of HOG-TT
    6.2.1 HOG descriptor
    6.2.2 HOG-TT
    6.3 Experimental Results
    6.4 Conclusions
    References
    Chapter 7 FF-TL: An Effective Tread Pattern Image Classification Algorithm Based on Transfer Learning
    7.1 Introduction
    7.2 Related Work
    7.2.1 Convolutional neural network
    7.2.2 Transfer learning
    7.3 Proposed Algorithm
    7.3.1 Fine-tuning the network
    7.3.2 Feature extraction, feature fusion and SVM classification
    7.4 Experimental Results
    7.4.1 Experimental dataset and performance evaluation parameter
    7.4.2 Experimental results and analysis
    7.5 Conclusions
    References
    Chapter 8 Summary and Future Work
    8.1 Summary of the Book
    8.2 Discussion of Future Work
    8.3 Acknowledgment
    Appendix 1: CIIP Tread Indentation Database
    Appendix 2: CIIP Tread Pattern Database

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