| 脉冲耦合神经网络在车牌定位中的应用 |
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| 引用本文： | 宋文强,马义德,何胜宗.脉冲耦合神经网络在车牌定位中的应用[J].计算机工程,2010,36(16):174-175. |
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| 作者姓名： | 宋文强 马义德 何胜宗 |
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| 作者单位： | 兰州大学信息科学与工程学院,兰州,730000 |
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| 基金项目： | 国家自然科学基金资助项目，国家大学生创新性实验计划基金资助项目 |
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| 摘 要： | 针对冗余边缘对基于边缘统计特征的车牌定位算法存在较严重干扰的问题，提出一种基于脉冲耦合神经网络(PCNN)的车牌定位方法。在借鉴传统算法的基础上，为抑制干扰性边缘，引入简化的PCNN模型，仅对候选区进行数次PCNN迭代运算，可大幅降低运算复杂度并提高车牌定位率。对300幅车辆图像进行仿真实验，取得了98.3%的定位率。
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| 关 键 词： | 边缘 车牌定位 脉冲耦合神经网络 |
Application of Pulsed Coupled Neural Network in Vehicle License Plate Location |
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| SONG Wen-qiang,MA Yi-de,HE Sheng-zong.Application of Pulsed Coupled Neural Network in Vehicle License Plate Location[J].Computer Engineering,2010,36(16):174-175. |
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| Authors: | SONG Wen-qiang MA Yi-de HE Sheng-zong |
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| Affiliation: | (School of Information Science and Engineering, Lanzhou University, Lanzhou 730000) |
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| Abstract: | To solve serious interference problems of redundant edges for edge-based statistical features of license plate location, a new vehicle license plate location method based on Pulsed Coupled Neural Network(PCNN) is proposed, which introduces the simplified PCNN model based on traditional license plate location algorithms. In the algorithm only the candidate area is produced by PCNN iteration in order to reduce the computational complexity and improve the rate of license plate location. Simulation experiments with 300 frames of vehicle license plate image that are taken under various kinds of conditions can get a 98.3% extraction rate. |
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| Keywords: | edge vehicle license plate location Pulsed Coupled Neural Network(PCNN) |
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