| 基于SVM分类器的集装箱箱号识别法 |
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| 引用本文： | 安博文,李丹,庞然.基于SVM分类器的集装箱箱号识别法[J].上海海事大学学报,2011,32(1):25-29. |
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| 作者姓名： | 安博文 李丹 庞然 |
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| 作者单位： | 上海海事大学信息工程学院,上海,201306 |
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| 基金项目： | 上海海事大学校基金(20100138) |
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| 摘 要： | 为准确、高效地识别集装箱箱号,提出基于支持向量机(Support Vector Machine,SVM)分类器的集装箱箱号识别法.在对大量箱号图片进行实验并统计各种特征识别率的基础上,经过预处理、箱号定位、字符分割,得到36×22像素大小的二值化图像;提取箱号字符的边界和质心特征、改进的灰度直方图特征以及边缘方向直方图...
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| 关 键 词： | 字符识别 支持向量机 质心特征 改进的灰度直方图特征 边缘方向直方图特征 |
| 收稿时间： | 2010/9/12 0:00:00 |
| 修稿时间： | 2010/12/22 0:00:00 |
Recognition method of container code based on SVM classifier |
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| AN Bowen,LI Dan,PANG Ran.Recognition method of container code based on SVM classifier[J].Journal of Shanghai Maritime University,2011,32(1):25-29. |
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| Authors: | AN Bowen LI Dan PANG Ran |
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| Institution: | AN Bowen,LI Dan,PANG Ran(Information Engineering College,Shanghai Maritime Univ.,Shanghai 201306,China) |
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| Abstract: | In order to recognize container code precisely and effectively, a recognition method of container code based on support vector machine (SVM) classifier is proposed. On the basis of experiment by using many container code images and count recognition rate of various features, binary images with size of 36×22 pixels are obtained by preprocessing, container code locating and character segmentation. The character features including edge, center of mass, improved grayscale histogram and edge direction histogram are extracted and combined into feature vector which is processed by dimensionality reduction and normalization. The processed feature vector is classified and recognized through SVM classifier. Experiment results show that the average recognition rate can reach 95%, which is higher than that of single feature recognition, simple template matching algorithm and weighted feature (8 neighborhood) template matching algorithm. |
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| Keywords: | character recognition support vector machine center of mass feature improved grayscale histogram feature edge direction histogram feature |
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