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Roadsign detection and recognition (RSDR)

机译:道路标志检测和识别(RSDR)

摘要

Road-sign Detection and Recognition via Video (RSDR) is a system that able to detect and recognize a road-sign on a motion video. This is due to the rapid changes of the technologies, more and more technologies recognize are able to provide high performance for people to carry their daily task. In RSDR, it is a system help the driver to recognize the shape of road-sign while the driving task is carried. Before this, most of the processing in digital image is based on still image. The limitation on still images is unable to perform effectively then motion video. Motion video can be processed directly in real-time by capturing the data to be examine, while for the still image the captured data is not in real-time thus the information cannot be delivered in short time. This RSDR will be developed according to methodology of waterfall models and it weakness is overcome by applied the incremental and iterative development process. Because with the well defined of the requirement on RSDR, the waterfall model is chooses to produce a high quality system. In case, there is some of the uncountable event occur required changes on development process the support of incremental and iterative development process can be help to overcome this problem arise. The method of template matching is used to recognize the road-sign. Before the recognition process, the detection of the road-sign on motion video is being done in Matlab by applied the Video and Image Processing techniques control by simulation process to detect an object from motion video. Only the successful of the object extracted from video frame will proceed to template matching on recognition process based on the template in the database. In conclusion, RSDR is potentially being a smart system in future for user to gather information from real-time process such as the driving task.
机译:通过视频的路标检测和识别(RSDR)是一种能够检测和识别运动视频上的路标的系统。这是由于技术的日新月异,越来越多的技术能够为人们执行日常任务提供高性能。在RSDR中,这是一个系统,可帮助驾驶员在执行驾驶任务时识别路标的形状。在此之前,数字图像中的大多数处理都是基于静止图像。静止图像的限制无法有效地发挥运动视频的作用。通过捕获要检查的数据可以直接实时处理运动视频,而对于静止图像,捕获的数据不是实时的,因此信息无法在短时间内传递。该RSDR将根据瀑布模型的方法进行开发,并通过应用增量迭代开发过程来克服其弱点。因为对RSDR的要求有明确的定义,所以选择瀑布模型来生成高质量的系统。万一发生某些不可数事件,需要在开发过程中进行更改,对增量和迭代开发过程的支持可以帮助克服这一问题的发生。模板匹配的方法用于识别路标。在识别过程之前,通过在Matlab中应用视频和图像处理技术(通过仿真过程进行控制)来从运动视频中检测对象,从而对运动视频上的路标进行检测。仅成功从视频帧中提取的对象将基于数据库中的模板进行识别过程中的模板匹配。总而言之,RSDR将来可能成为智能系统,供用户从诸如驾驶任务之类的实时过程中收集信息。

著录项

  • 作者

    Lim Chin Huey;

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  • 年度 2010
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