交通标志识别算法模型的研究与实现

Research and Implementation of Traffic Sign Recognition Algorithm

本文通过比较交通标志检测和分类算法,利用阈值分割和神经网络算法思想构建了一个交通标志识别模型,该模型对于GTSRB数据集上的交通标志识别图片识别错误率能控制在5%以内,处理每帧的识别过程在150ms左右,较好地实现了交通标志的实时检测与分类。为相关交通管理部门提供了一套方便的管理技术。

In this paper,by comparing the traffic sign detection and classification algorithm,using the ideas of threshold segmentation algorithm and neural network,researchers constructed a traffic sign recognition model,the model for GTSRB data sets on traffic sign recognition image recognition error rate can be controlled within5%,the processing of each frame recognition process is controlled in150ms,implement the real-time detection and classification of traffic signs well.The researchers provided a convenient management technology for related traffic management department.