论文标题
根据图像颜色组件的模板匹配的自动实时车辆分类
Automatic Real-time Vehicle Classification by Image Colour Component Based Template Matching
论文作者
论文摘要
选择适当的模板匹配算法以在实时低成本系统上有效运行始终是主要问题。这是由于图像场景的不可预测的变化，通常需要更复杂的实时算法来保留图像一致性。低成本辅助硬件和时间限制的效率低是使用这些算法的主要限制。此处介绍的实时系统使用快速运行的模板匹配算法来应对这些问题，该模板使用最佳的色带选择。该系统使用快速运行的实时算法来实现大约4帧 /秒的模板匹配和车辆分类。在低成本硬件上。颜色图像序列是由固定的CCTV摄像头俯瞰繁忙的多车道道路
Selection of appropriate template matching algorithms to run effectively on real-time low-cost systems is always major issue. This is due to unpredictable changes in image scene which often necessitate more sophisticated real-time algorithms to retain image consistency. Inefficiency of low cost auxiliary hardware and time limitations are the major constraints in using these sorts of algorithms. The real-time system introduced here copes with these problems utilising a fast running template matching algorithm, which makes use of best colour band selection. The system uses fast running real-time algorithms to achieve template matching and vehicle classification at about 4 frames /sec. on low-cost hardware. The colour image sequences have been taken by a fixed CCTV camera overlooking a busy multi-lane road
