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
翻译:选择适当的模板匹配算法,以便在实时低成本系统上有效运行,这始终是一个主要问题,原因是图像场景的不可预测的变化,往往需要更复杂的实时算法,以保持图像的一致性。低成本辅助硬件和时间限制效率低下是使用这类算法的主要制约因素。这里采用的实时系统处理这些问题,使用快速运行模板匹配算法,使用最佳色带选择法。该系统使用快速运行实时算法,在大约4个框架/秒的低成本硬件上实现模板匹配和车辆分类。彩色图像序列由固定的闭路电视摄像头拍摄,而忽略了繁忙的多车道。