Grid-based real-time image processing (GRIP) algorithm for heterogeneous traffic

S. Manipriya, Gitakrishnan Ramadurai, V. Reddy
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引用次数: 9

Abstract

The paper presents a fast algorithm for real-time image processing for counting and classification of vehicles in heterogeneous traffic recorded using a single stationary camera. The proposed method uses a single feature as the base parameter which is given by the user to classify the vehicles into four different classes. The algorithm has an error of 6.1% on an average for the total count when studied under varying illumination and weather conditions.
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基于网格的异构流量实时图像处理(GRIP)算法
本文提出了一种快速的实时图像处理算法,用于单台固定摄像机记录的异构交通中车辆的计数和分类。该方法使用用户给出的单个特征作为基参数,将车辆分为四类。该算法在不同光照和天气条件下的总计数平均误差为6.1%。
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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