Y. Sari, A. Baskara, Khair Zuniar Rahman, P. B. Prakoso
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引用次数: 0
摘要
交通堵塞,缺乏足够的交通信息用于道路基础设施的发展,以减少交通堵塞,以及在执行繁重的交通调查的人为错误的可能性成为本研究的主要背景。利用信息技术,为基于计算机视觉的监控系统的发展开辟了契机。本研究将基于分阶段ROI选择、高斯混合模型方法的图像分割、滤波处理、blob检测与跟踪、模糊聚类方法的车辆分类,利用计算机视觉计算基于类型的移动车辆总量。使用visual studio 2010实现一个应用程序。输出包括分类结果和基于其类型的车辆总量。测试应用程序分为几个测试场景,即测试1、测试2、测试3和测试4。各测试的准确率分别为36.27%、50.47%、60.75%和67.00%。
Counting the Number of Moving Vehicles by Its Type Based on Computer Vision
Traffic jam, lack of adequate information of the traffic low used for development of road infrastructure to reduce traffic jam, and possibility of human error in the execution of a heavy traffic survey become the primary background of this study. By using information technology, open up an opportunity for the development of monitoring system computer vision based. This study will calculate the total amount of moving vehicles based on its type with computer vision based with staged: ROI selection, image segmentation with Gaussian Mixture Model method, filtering process, blob detection and tracking, and vehicles classification with Fuzzy Clustering Means. Implementation of an application using visual studio 2010. The output comprises result of classification and total amount vehicles based on its type. The test application divided into a few test scenarios, namely test 1, test 2, test 3 and test 4. The accuracy obtained on each test are 36.27%, 50.47%, 60.75%, and 67.00% respectively.