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Implementation of Dynamic Time Warping Method for the Vehicle Number License Recognition

机译:动态时间规整方法在车号识别中的实现

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In the era of information technology vehicle numbers identification needs to be done by system automatically. Therefore, the accuracy of the data is well documented and work porses identification can be done quickly. Motor vehicle license recognition is a recognition system by comparing character feature in license plate with reference feature which exists in database. This system uses chain code method and template matching to extract character feature in license plate’s image. Feature extraction with chain code method will result in an array of direction codes which stored in dynamic array, which stored in dynamic array. In this application test feature will be matched with feature stored in database using dynamic time warping method (DTW) to obtain a distance value between test feature and reference feature, the smaller the distance obtained shows that both the features are more similar. The result of this system is the recognition of each character in license plate’s image. In this study, samples of license plate’s images are tested with the number of research objects. From the study feature extraction is obtained with template matching method provides better success rate compared to feature extraction with chain code method, where the success rate of feature extraction with template matching method is at 78% whereas feature extraction with chain code method is at 68%.
机译:在信息技术时代,车辆号码识别需要由系统自动完成。因此,数据的准确性得到了很好的证明,并且可以快速完成工作流程的识别。机动车牌照识别是一种通过将车牌中的字符特征与数据库中存在的参考特征进行比较的识别系统。该系统使用链式编码方法和模板匹配来提取车牌图像中的字符特征。使用链码方法进行特征提取将导致将方向码数组存储在动态数组中,并将其存储在动态数组中。在此应用程序中,将使用动态时间规整方法(DTW)将测试要素与存储在数据库中的要素进行匹配,以获取测试要素与参考要素之间的距离值,所获得的距离越小,表明两个要素越相似。该系统的结果是识别车牌图像中的每个字符。在这项研究中,对车牌图像的样本与许多研究对象进行了测试。通过研究,与链码方法进行特征提取相比,模板匹配方法获得的特征提取成功率更高,模板匹配方法进行特征提取的成功率为78%,链码方法进行特征提取的成功率为68% 。

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