首页> 外国专利> TRAFFIC-LIGHT DETECTION AND CLASSIFICATION USING COMPUTER VISION AND DEEP LEARNING.

TRAFFIC-LIGHT DETECTION AND CLASSIFICATION USING COMPUTER VISION AND DEEP LEARNING.

机译:使用计算机视觉和深度学习对交通灯进行检测和分类。

摘要

A method is disclosed for detecting and classifying one or more traffic lights. The method may include converting an RGB frame to an HSV frame. The HSV frame may be filtered by at least one threshold value to obtain at least one saturation frame. At least one contour may be extracted from the at least one saturation frame. Accordingly, a first portion of the RGB may be cropped in order to encompass an area including the at least one contour. The first portion may then be classified by an artificial neural network to determined whether the first portion corresponds to a not-a-traffic-light class, a red-traffic-light class, a green-traffic-light class, a yellow-traffic-light class, or the like.
机译:公开了一种用于检测和分类一个或多个交通信号灯的方法。该方法可以包括将RGB帧转换为HSV帧。可以将HSV帧滤波至少一个阈值以获得至少一个饱和帧。可以从至少一个饱和度帧中提取至少一个轮廓。因此,可以裁剪RGB的第一部分以便包围包括至少一个轮廓的区域。然后可以通过人工神经网络对第一部分进行分类,以确定第一部分是否对应于非交通灯类别,红色交通灯类别,绿色交通灯类别,黄色交通灯类别。 -light class等。

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