Research of the Real-Time Detection of Traffic Flow Based on OpenCV

Z. Lei, Zhang Xue-fei, Liu Yin-ping
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引用次数: 16

Abstract

A vehicle detection algorithm was proposed based on the morphology and wavelet transform, in the context of the traditional difference. First, the background model was established, using statistical means of the rapid sequence. As background to transform the impact of light obviously, the corresponding easy and quick to update the background algorithm was used. Using the background of the video images to do background subtraction, and then images of the vehicles were accurate detection of mathematical morphology and wavelet transform. A video vehicle detection system was developed using visual C++6.0 and OpenCV image and development kits. A highway traffic flow has been detected by a background extraction, image filtering, image binary, morphological transformation, vehicle detection and segmentation methods and steps. To achieve some highway traffic flow analysis, results showed that: the system to identify the correct rate of more than 98 percent, satisfying the requirements of practical applications.
基于OpenCV的交通流实时检测研究
在传统差分方法的基础上,提出了一种基于形态学和小波变换的车辆检测算法。首先,利用快速序列的统计方法建立背景模型;由于背景变换对光线的影响明显,因此采用了相应的简单快速的背景更新算法。利用视频图像的背景进行背景相减,然后对图像中的车辆进行数学形态学和小波变换的精确检测。利用visual c++ 6.0和OpenCV图像及开发工具开发了视频车辆检测系统。本文介绍了高速公路交通流检测的主要方法和步骤,包括背景提取、图像滤波、图像二值化、形态变换、车辆检测和分割等。以某高速公路交通流分析为例,结果表明:系统识别正确率达98%以上,满足实际应用要求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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