基于彩色图像检测的车牌自动分割与识别

发布时间：2021-03-13 17:42

　　在我们的日常生活中,客运和货运都离不开车辆。自动车牌分割与识别（AVLPSR）技术是智能交通系统（ITS）的关键技术之一。目前,AVLPSR技术已广泛应用于停车场、自动收费、门禁、交通执法、过境管制、交通监控等多种现实应用场景,并且在各个领域都取得了良好的效果。中国标准车牌有多种类型,车牌的构成涉及38个汉字、24个大写英文字母（字母O和I除外）和1 0个数字（临时车牌除外）。AVLPSR方法可以利用图像处理技术车辆图像来检测车牌信息。在AVLPSR技术中,最重要也是最困难的一步是对车牌信息的分割,分割的准确度将直接影响到识别的结果。图像中一些干扰因素如灰尘、雨水、不适当的照明、雾和昏暗的光线条件等,将会使识别工作更加困难。在车牌图像识别车牌中,车牌分割法是从车牌中提取重要数据的一种方法。汽车牌照图像的自动识别是汽车牌照应用领域面临的挑战,主要难点在于颜色、字体、尺寸遮挡、位置和不同车牌种类等因素。本文的研究工作主要集中在对中国汽车牌照的检测、分割和识别。AVLPSR的主要过程分为三个步骤:车牌检测、字符分割和字符识别。本文提出了一种简单的车牌检测算法利用局部二值模式直方图（LBPH）... 

【文章来源】：北京邮电大学北京市 211工程院校 教育部直属院校

【文章页数】：81 页

【学位级别】：硕士

【文章目录】：
Abstract
摘要
List of Abbreviations
Chapter 1 Introduction
    1.1 Introduction
    1.2 System Components and Working
    1.3 Detection Background and Techniques
        1.3.1 Object Detection History
        1.3.2 Artificial Neural Network
        1.3.3 Convolutional Neural network algorithm
        1.3.4 Region Based Convolutional Neural Network
        1.3.5 Fast Region Based Convolutional Neural Network
        1.3.6 Faster Region Based Convolutional Neural
    1.4 Segmentation Background and Techniques
        1.4.1 K-means Clustering Algorithm
        1.4.2 Otsu Threshold Algorithm
        1.4.3 Global Thresh holding Algorithms
            1.4.3.1 Histogram based
            1.4.3.2 Clustering based
            1.4.3.3 Entropy based
            1.4.3.4 Gaussian Distributions
            1.4.3.5 Feature Extraction
        1.4.4 K nearest neighbors
    1.5 Recognition Background and Techniques
        1.5.1 Soft Computing Techniques
        1.5.2 Fuzzy Logic
        1.5.3 Template Matching Algorithm
        1.5.4 Structural/Syntactic Algorithm
    1.6 Motivation
    1.7 Summary
Chapter 2 Literature Review
    2.1 Introduction
    2.2 Related Research
    2.3 Literature Survey
    2.4 Problem Statement
Chapter 3 Research Methods of Segmentation and Recognition for Vehicle License PlateDetection
    3.1 Introduction
    3.2 Vehicle License Plate Detection
        3.2.1 Local Binary Pattern Algorithm used for Vehicle License Plate Detection
        3.2.2 Introduction
    3.3 Vehicle License Plate Segmentation
        3.3.1 Connected components algroithm
        3.3.2 Algorithm 1:Information Extracting
        3.3.3 Algorithm 2:Select primary and secondary components
        3.3.4 Algorithm 3:Assign secondary to primary components and output characters of Number Plates
    3.4 Vehicle License Plate Recognition
        3.4.1 Support Vector Machine
    3.5 Summary
Chapter 4 Results and Performance Analysis
    4.1 Software Used
        4.1.1 NetBeans
        4.1.2 Java
        4.1.3 MATLAB
        4.1.4 Jet Brain PyCharm:
        4.1.5 Python
    4.2 Vehicle License Plate Detection
    4.3 Vehicle License Plate Segmentation
    4.4 Vehicle License Plate Recognition
    4.5 Summary
Chapter 5 Conclusion and future work
    5.1 Conclusion
    5.2 Scope and Future Work
References
Acknowledgement
List of Publications



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