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Design of Traffic Sign Detection and Recognition Algorithm Based on Template Matching

机译:基于模板匹配的交通符号检测与识别算法设计

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In the field of automobile unmanned driving and assisted driving, the algorithms of traffic sign detection and recognition are extremely important, and the performance of these algorithms directly affects the driving safety of motor vehicles in road traffic. Especially today, it is necessary to ensure the accuracy, real-time, stability and anti-interference of traffic sign recognition, which have always been the focus of research. The new algorithm mainly performs the following tasks for the detection and recognition of traffic signs: first, the image is preprocessed to improve the image quality and reduce the amount of data. The image preprocessing mainly includes grayscale, image enhancement, image restoration and binarization; Secondly, we need to perform edge detection on the traffic sign image, and use color segmentation to roughly segment the image of interest; next, we perform morphological processing on the part obtained by the rough segmentation, and use shape segmentation to eliminate unnecessary interference, so that we can obtain Interested part; Finally, the final cut traffic signs are compared with the template library for recognition. The simulation results show that the algorithm in this paper can effectively recognize the traffic sign images, which can greatly improve the recognition rate and has extremely broad development prospects and research value.
机译:在汽车无人驾驶和辅助驾驶领域,交通标志检测和识别的算法非常重要,这些算法的性能直接影响道路交通中机动车辆的驱动安全性。特别是今天,有必要确保交通标志识别的准确性,实时,稳定性和抗干扰,这一直是研究的重点。新算法主要执行以下任务,用于检测和识别流量标志:首先,预处理图像以提高图像质量并减少数据量。图像预处理主要包括灰度,图像增强,图像恢复和二值化;其次,我们需要在交通标志图像上执行边缘检测,并使用颜色分割以大致分段感兴趣的图像;接下来,我们对粗略分割获得的部分进行形态处理,并使用形状分割来消除不必要的干扰,使我们能够获得感兴趣的部分;最后,将最终剪切交通标志与模板库进行比较以进行识别。仿真结果表明,本文的算法可以有效识别交通标志图像,这可以大大提高识别率,具有极大的发展前景和研究价值。

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