Potholes Road Classification by Shape and Area Features

Yesy Diah Rosita, S. Sugianto
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Abstract

Background of the study: Generally, during the rainy season, many potholes asphalt road are found. The high rainfall results in the fragile contour of the asphalt road and triggers a traffic accident. In the last decade, the development of potholes asphalt road detection has various method approaches.Purpose:  The research used precision to get a performance of the system.Method: In this study, the development system can classify potholes asphalt road by a simple algorithm. It also considers the time and space complexity.Findings: The algorithms as possible and only uses the handy-camera device to capture data which the level of performance as good as the results of previous research. Capturing data is also various distances with 450 point angles. For classification steps, the system applied two main features, area and shape feature of the object. The used parameters for these features are the length of major and minor axis object. It used to calculate area and eccentricity values.Conclusion: In conclusion, the experiment result reaches 81.696% of the 1125 frames used.
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坑洼道路的形状和面积特征分类
研究背景:一般来说,在雨季,沥青路面会出现许多凹坑。高降雨量导致沥青路面轮廓脆弱,引发交通事故。近十年来,沥青路面凹坑检测的发展有多种方法途径。目的:本研究利用精度对系统进行性能分析。方法:在本研究中,开发系统可以通过简单的算法对沥青路面凹坑进行分类。它还考虑了时间和空间的复杂性。研究结果:该算法尽可能且仅使用便携式相机设备捕获数据,其性能水平与以往研究结果相当。捕获数据也以450个角的不同距离。在分类步骤中,系统应用了两个主要特征:物体的面积和形状特征。这些特征使用的参数是长轴和小轴对象的长度。它用于计算面积和偏心率值。结论:综上所述,实验结果达到了所用1125帧的81.696%。
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