基于距离图像的车辆分类系统

Shiquan Peng, C. Harlow
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引用次数: 7

摘要

在这个项目中,我们考虑自动车辆定位和分类系统。目前使用环路探测器或摄像机的系统存在缺陷。基于视频的系统对环境条件比较敏感,在车辆分类中表现不佳。正在开发的新一代距离或距离传感器提供了对照明条件不敏感的传感器,并且提供的信息应该比现有系统提供更好的车辆检测和分类百分比。该项目的重点是开发基于距离传感器获得的图像的自动车辆定位和分类系统。开发了用于车辆分类的图像分析算子和分类方法。初步结果表明,该方法可以获得准确的车辆分类。
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A system for vehicle classification from range imagery
In this project we consider automated vehicle location and classification systems. Current systems which utilize loop detectors or video cameras have deficiencies. Video based systems are sensitive to environmental conditions and do not perform well in vehicle classification. The new generation of range or distance sensors that are being developed offer the promise of sensors which are not sensitive to lighting conditions and provide information which should give better vehicle detection and classification percentages than current systems. The focus of this project is to develop an automated vehicle location and classification system based upon imagery obtained from range sensors. Image analysis operators and classification methods are developed for vehicle classification. Preliminary results indicate that accurate vehicle classification can be obtained.
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