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   license plate detection 的翻译结果: 查询用时:0.174秒
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license plate detection
相关语句
  车牌检测
     License Plate Detection Based on Adaboost Algorithm
     基于adaboost算法的车牌检测
短句来源
     Real-time License Plate Detection Based on Hierarchical Distances Between Neighboring Edge Points
     基于分级边缘间距的实时车牌检测
短句来源
     The paper presents a new method of license plate detection based on fuzzy set by employing color characteristics and texture characteristics of the license plate in the module of license plates detection.
     在车牌检测模块中,本文利用车牌的颜色特征与纹理特征,提出一种新的基于模糊集的车牌定位方法。
短句来源
     The license plate detection turned out to be the key technology in the LPR,plate image's detection exist perplexities due to the noise,plate inclination,illumination variance,motion illegibility.
     车牌检测是LPR中的关键技术。 车牌图像由于受到噪声、车牌倾斜、光照不均、运动模糊等的影响,检测存在着很大的困难。
短句来源
  “license plate detection”译为未确定词的双语例句
     Being a special computer vision system in the real-time case, the LPR system mainly includes the subsystem of license plate detection and character recognition.
     作为一个综合的实时计算机视觉系统,汽车牌照识别技术主要包括牌照定位和牌照识别两个部分。
短句来源
     Being a special computer vision system in the real-time case, the LPR (License Plate Recognition) system mainly includes the subsystem of license plate detection and character recognition.
     车辆牌照识别系统作为一个综合的实时计算机视觉系统主要包括车牌照定位分割和车牌照字符识别两个部分。
短句来源
     This paper presents a novel algorithm for license plate detection in complex environments.
     提出一种在复杂环境下进行实时车牌定位的新方法。
短句来源
  相似匹配句对
     Algorithms for Segmentation of License Plate
     车牌字符分割算法的比较研究
短句来源
     License Plate Dynamic Recognition
     汽车牌照的动态识别
短句来源
     License Plate Detection Based on Adaboost Algorithm
     基于adaboost算法的车牌检测
短句来源
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  license plate detection
We presented a license plate detection method based on a novel descriptor.
      
We impose the license plate detection as a classifier based binary recognition problem.
      
We present a license plate detection algorithm that employs a novel image descriptor.
      
To justify the application of the Viola-Jones detector, we apply it on the very popular task of License Plate Detection.
      
If enough samples are acquired a neural networkbased approach may be tested for license plate detection.
      
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The issue of car license plate recognition is a focus direction of studying both at home and abroad at present, its success has important application values in vehicle controlling, transportation management, parking and so-so. There are many papers published in the research domain. In order to solve the primary problem of the car license plate recognition--Automatic orientation technology of the car license plates, a method of automatic detection and orientation of car license plate based on license plate's...

The issue of car license plate recognition is a focus direction of studying both at home and abroad at present, its success has important application values in vehicle controlling, transportation management, parking and so-so. There are many papers published in the research domain. In order to solve the primary problem of the car license plate recognition--Automatic orientation technology of the car license plates, a method of automatic detection and orientation of car license plate based on license plate's projection invariability in the condition of lesser deflection of car license is presented in terms of the imaging characteristics of the car license plate target, which can succeed in detecting and orienting the car license plate from the complicated background. Tested actually through the scene, the method obtains satisfactory localization effect. In the end of the paper, some experimental results are given out. In virtue of the successful car license plate detection and localization, it is possible for license plate number extraction and recognition.

车牌识别问题是当前国内外研究的一个热点方向 ,它的研究成功对车辆控制、运输安排等有着重要的应用价值 .为了解决车牌识别中的首要问题——车牌的自动定位技术 ,根据车牌目标在图象中的成像特点 ,提出了基于投影不变性的车牌自动检测定位方法 ,在车牌歪斜角度不大的情况下 ,成功地从复杂背景中检测定位出了车牌 .通过现场实际测试 ,该方法取得了较好的定位识别效果 .

License Plate Recognition(LPR) proved an crucial researching issue in Intelligent Traffic System(ITS).The LPR's automatic recognition consists of three sections: license plat detection,character segmentation and character recognition.The license plate detection turned out to be the key technology in the LPR,plate image's detection exist perplexities due to the noise,plate inclination,illumination variance,motion illegibility.Hence,the essay summarized merits and demerits of ascendants...

License Plate Recognition(LPR) proved an crucial researching issue in Intelligent Traffic System(ITS).The LPR's automatic recognition consists of three sections: license plat detection,character segmentation and character recognition.The license plate detection turned out to be the key technology in the LPR,plate image's detection exist perplexities due to the noise,plate inclination,illumination variance,motion illegibility.Hence,the essay summarized merits and demerits of ascendants based on computation,proposing a new detecting approach based on adaboost algorithm,the advantage of which revealed high detection rate,less time consuming and chronic adaptability.

车牌识别技术(LPR)是智能交通(ITS)领域的重要研究课题之一。车牌的自动识别分为车牌检测、字符分割、字符识别三个主要部分。车牌检测是LPR中的关键技术。车牌图像由于受到噪声、车牌倾斜、光照不均、运动模糊等的影响,检测存在着很大的困难。因此,在总结前人检测算法的优点和缺点的基础上,提出了基于adaboost算法的检测算法,其优点是检测率高,检测时间少,适应性特别强。

This paper presents a novel algorithm for license plate detection in complex environments.The algorithm generates connective components by hierarchical distances between edge points based on vehicle edge map and then gets the relevant minimum enclosing rectangular by searching the whole map.Afterwards,it picks up candidate regions of plates according totopological characteristics and color features.In this paper,least constraints are imposed on the working environment.In the experiment for locating...

This paper presents a novel algorithm for license plate detection in complex environments.The algorithm generates connective components by hierarchical distances between edge points based on vehicle edge map and then gets the relevant minimum enclosing rectangular by searching the whole map.Afterwards,it picks up candidate regions of plates according totopological characteristics and color features.In this paper,least constraints are imposed on the working environment.In the experiment for locating license plates,526 images taken from various scenes and under different conditions were processed with an accuracy of 98.3%.At the same time,the average locating time is less than 40ms.

提出一种在复杂环境下进行实时车牌定位的新方法。先根据车牌图像的边缘特征,利用多级边缘点距离生成连通区域,搜索全图得到连通域的最小外接矩形。然后利用车牌本身的拓扑特征和颜色特征进行判别,提取候选区域。与同类方法相比,该方法限制条件少、速度快、准确率高。对526幅各种环境下实际采样图像进行实验,定位成功率为98.3%,平均定位时间少于40m s。

 
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