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Based on The Centerline of The Closed-loop Control Map Information Identification and Extraction

机译:基于中心线的闭环控制图信息识别与提取

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This Paper introduces a feedback closed loop method to automatically recognition and extraction roads from color city maps, in order to recognition and extraction full the road network .Based on approach thought of microscopic identification and macroscopic elimination, the system realized first the road layer initial recognition and last road map level completely to withdraw via some output layers reclustering and feedback control. In view of the standard municipal transportation map, the path and the region valve value condition has determined. Through re-clustering to the noise the whole map can be completely divided into two parts of road and nonroad(region). The feedback re-clustering strategies of recognition for the transportation road networks are based on the core characteristic of obtained road constitution. The convergence of the feedback reclustering of road layer guarantees the map level optimization. The experiments prove this method to be an efficient method with advantages of precision, automation and broad use.
机译:本文介绍了一种反馈闭环方法,用于从彩色城市地图中自动识别和提取道路,以便对整个道路网络进行识别和提取。基于微观识别和宏观消除的思路,系统首先实现了道路层的初始识别最后的路线图级别则完全可以通过一些输出层的重新编组和反馈控制来撤消。根据标准的市政运输地图,已确定路径和区域阀门值条件。通过对噪声进行重新聚类,可以将整个地图完全分为道路和非道路(区域)两部分。交通路网识别的反馈聚类策略基于获得的道路构成的核心特征。道路图层反馈聚类的收敛性保证了地图级的优化。实验证明,该方法是一种精度高,自动化程度高,用途广泛的有效方法。

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