一种应用于汽车交通道路标志的增强目标检测方法

Anass Barodi, Abdrrahim Bajit, M. Benbrahim, A. Tamtaoui
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引用次数: 9

摘要

在本文中,我们使用其中最著名的库是开放计算机视觉,我们将其简称为OpenCV。它用于图像处理,做我们想做的所有操作,隔离和检测一个特定的物体,在我们的例子中是交通道路标志。我们力求找到最有效的交通道路标志检测方法。我们的目标是展示优化和强大的元素与计算机视觉算法的联系,这些算法易于使用,如在图像和视频处理中键入。他们主要采用颜色选择、边缘检测、兴趣区域选择和形状变换检测等技术。许多应用需要识别城市地区的交通道路标志。这项任务的自动化是必要的,例如,ADAS系统和视觉机器人或自动驾驶汽车的应用,包括尽可能快地识别和识别交通道路标志,并将错误降到最低,这些图像是由车载嵌入式摄像头获取的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Enhanced Approach in Detecting Object Applied to Automotive Traffic Roads Signs
In this article, we use among and the best-known library is Open Computer Vision we call it for short OpenCV. It is used for image processing, to do all operations we want, to isolate and detect a specific object, which in our case are traffic road signs. We process to find the most efficient methods of detection of traffic road signs. Our objective is to demonstrate the links the elements for optimized and powerful to computer vision algorithms that are easy to use as typing in an image and video processing. Most of the techniques they employed the color selection, edge detection, a region of interest selection, and shapes transformation of detection. Many applications require the recognition of traffic road signs in urban areas. The automation of this task is necessary, for example, ADAS systems, and the application of vision robotics or an autonomous vehicle, consist of recognizing and identifying traffic road signs as quickly as possible with errors to be minimized, in images of their type acquired by an embedded camera on board a vehicle.
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