首页    期刊浏览 2024年09月15日 星期日
登录注册

文章基本信息

  • 标题:Potholes Road Classification by Shape and Area Features
  • 本地全文:下载
  • 作者:Yesy Diah Rosita ; Sugianto Sugianto
  • 期刊名称:Record and Library Journal
  • 电子版ISSN:2442-5168
  • 出版年度:2019
  • 卷号:5
  • 期号:1
  • 页码:72-79
  • DOI:10.20473/rlj.V5-I1.2019.72-79
  • 出版社:Universitas Airlangga
  • 摘要: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.
  • 其他摘要: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.
  • 关键词:area; classification; pothole; shape
  • 其他关键词:potholes asphalt road; area; eccentricity; digital
国家哲学社会科学文献中心版权所有