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A Novel Morphological Method for Detection and Recognition of Vehicle License Plates | Science Publications

机译:检测和识别车牌的一种新的形态学方法科学出版物

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> Problem statement: License plate detection and recognition is an image-processing technique used to identify a vehicle by its license plate. This notable technology has got multiple applications in various traffic and security cases. To name but a few, toll roads, border control, security and car tracking are same of its applications. The main stage is the isolation of the license plate, from the digital image of the car obtained by a digital camera under different circumstances such as illumination, slop, distance and angle. Approach: This study presented a novel method of identifying and recognizing license plates based on the morphology and template matching. The algorithm started with reprocessing and signal conditioning. Next license plate is localized using morphological operators. Then a template matching scheme will be used to recognize the digits and characters within the plate. Results: The system was tested on Iranian car plate images and the performance was 97.3% of correct plates identification and localization and 92% of correct recognized characters. The results regarding the complexity of the problem and diversity of the test cases showed the high accuracy and robustness of the proposed method. The method could also be applicable for other applications in the transport information systems, where automatic recognition of registration plates, shields, signs and so on is often necessary. Conclusion: This system was customized for the identification of Iranian license plates. The results showed that this algorithm performs well on different types of vehicles including Iranian car and motorcycle plates as well as diverse circumstances. We believe that this system can be redesigned and tested for multi national car license plates in the future time regarding their own attributes.
机译: > 问题陈述:车牌检测和识别是一种图像处理技术,用于通过车牌识别车辆。这项引人注目的技术已在各种流量和安全情况下获得了多种应用。仅举几例,收费公路,边境管制,安全和汽车跟踪与它的应用相同。主要阶段是将车牌与数字相机在不同情况下(例如照明,倾斜,距离和角度)获得的汽车数字图像隔离。 方法:这项研究提出了一种基于形态和模板匹配的识别和识别车牌的新方法。该算法从重新处理和信号调理开始。使用形态运算符将下一个车牌定位。然后,将使用模板匹配方案来识别车牌内的数字和字符。 结果:该系统在伊朗汽车车牌图像上进行了测试,其性能为正确车牌识别和定位的97.3%,正确识别字符的92%。有关问题复杂性和测试案例多样性的结果表明,该方法具有较高的准确性和鲁棒性。该方法还可以适用于运输信息系统中的其他应用,在这些应用中,经常需要自动识别车牌,盾牌,标志等。 结论:该系统是为识别伊朗车牌而定制的。结果表明,该算法在不同类型的车辆(包括伊朗的汽车和摩托车车牌)以及不同的环境下都能表现良好。我们相信,针对自己的属性,将来可以针对多国汽车牌照对该系统进行重新设计和测试。

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