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Fast Vision-Based Pedestrian Traffic Light Detection

机译:基于快速视觉的行人交通信号灯检测

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摘要

Detection of pedestrian traffic light is very important for the visually impaired. However, fast but accurate vision-based detection is not an easy task due to the complexity of background and illumination. In this paper, a fast vision-based detection system is designed. In the designed system, the background filter is applied to identify the candidate regions of pedestrian traffic lights. And the cascade classifier obtained by the Adaboost algorithm based on the multi-layer features is used to detect the pedestrian traffic lights. Testing results verifies the effectiveness of the designed system.
机译:对行人交通信号灯的检测对于视障者来说非常重要。但是,由于背景和照明的复杂性,快速但准确的基于视觉的检测并非易事。本文设计了一种基于快速视觉的检测系统。在设计的系统中,背景滤镜被应用于识别行人交通信号灯的候选区域。基于多层特征的Adaboost算法获得的叶栅分类器用于检测行人交通信号灯。测试结果验证了所设计系统的有效性。

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