{"title":"基于计算机视觉的瓷砖排水流出率估计方法","authors":"Sierra N. Young, Meng Han, J. Peschel","doi":"10.13031/aea.15157","DOIUrl":null,"url":null,"abstract":"HighlightsVision-based approach for detecting outlet flow of tile drains in a laboratory environment.Method accurately detects and estimates flow within 12% or less of ground truth flow rate.A real-time application was developed that provides estimated flow rates from collected video.Abstract. This article presents a computer vision-based approach for monitoring water flow at outlet points of a tile drain system. The approach relies only on video capture of events at outlet points, thus a camera can be installed remotely and without contact with water. The algorithm detects, identifies, and tracks flows by motion, shape, and color features and measures flow rate based on a proposed model and two provided dimensions. The software was tested in a laboratory environment with three different target flow rate conditions: 0.312, 0.946, and 1.58 L/s (5, 15, and 25 gal/min). Flow rates reported by the computer vision approach are within 12% of the ground-truth flow rate baseline. The results of this work show that computer vision can be used as a reliable method for monitoring outlet flows from free-standing outlet structures under laboratory conditions. This work opens the possibility of applying computer vision techniques in tile drain monitoring from outlet points with mobile video recording devices in the field. Keywords: Keywords., Morphological transformations, Outflow detection, Outlet flow, Real-time application.","PeriodicalId":55501,"journal":{"name":"Applied Engineering in Agriculture","volume":null,"pages":null},"PeriodicalIF":0.8000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Computer Vision Approach for Tile Drain Outflow Rate Estimation\",\"authors\":\"Sierra N. Young, Meng Han, J. Peschel\",\"doi\":\"10.13031/aea.15157\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"HighlightsVision-based approach for detecting outlet flow of tile drains in a laboratory environment.Method accurately detects and estimates flow within 12% or less of ground truth flow rate.A real-time application was developed that provides estimated flow rates from collected video.Abstract. This article presents a computer vision-based approach for monitoring water flow at outlet points of a tile drain system. The approach relies only on video capture of events at outlet points, thus a camera can be installed remotely and without contact with water. The algorithm detects, identifies, and tracks flows by motion, shape, and color features and measures flow rate based on a proposed model and two provided dimensions. The software was tested in a laboratory environment with three different target flow rate conditions: 0.312, 0.946, and 1.58 L/s (5, 15, and 25 gal/min). Flow rates reported by the computer vision approach are within 12% of the ground-truth flow rate baseline. The results of this work show that computer vision can be used as a reliable method for monitoring outlet flows from free-standing outlet structures under laboratory conditions. This work opens the possibility of applying computer vision techniques in tile drain monitoring from outlet points with mobile video recording devices in the field. Keywords: Keywords., Morphological transformations, Outflow detection, Outlet flow, Real-time application.\",\"PeriodicalId\":55501,\"journal\":{\"name\":\"Applied Engineering in Agriculture\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applied Engineering in Agriculture\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://doi.org/10.13031/aea.15157\",\"RegionNum\":4,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"AGRICULTURAL ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Engineering in Agriculture","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.13031/aea.15157","RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"AGRICULTURAL ENGINEERING","Score":null,"Total":0}
Computer Vision Approach for Tile Drain Outflow Rate Estimation
HighlightsVision-based approach for detecting outlet flow of tile drains in a laboratory environment.Method accurately detects and estimates flow within 12% or less of ground truth flow rate.A real-time application was developed that provides estimated flow rates from collected video.Abstract. This article presents a computer vision-based approach for monitoring water flow at outlet points of a tile drain system. The approach relies only on video capture of events at outlet points, thus a camera can be installed remotely and without contact with water. The algorithm detects, identifies, and tracks flows by motion, shape, and color features and measures flow rate based on a proposed model and two provided dimensions. The software was tested in a laboratory environment with three different target flow rate conditions: 0.312, 0.946, and 1.58 L/s (5, 15, and 25 gal/min). Flow rates reported by the computer vision approach are within 12% of the ground-truth flow rate baseline. The results of this work show that computer vision can be used as a reliable method for monitoring outlet flows from free-standing outlet structures under laboratory conditions. This work opens the possibility of applying computer vision techniques in tile drain monitoring from outlet points with mobile video recording devices in the field. Keywords: Keywords., Morphological transformations, Outflow detection, Outlet flow, Real-time application.
期刊介绍:
This peer-reviewed journal publishes applications of engineering and technology research that address agricultural, food, and biological systems problems. Submissions must include results of practical experiences, tests, or trials presented in a manner and style that will allow easy adaptation by others; results of reviews or studies of installations or applications with substantially new or significant information not readily available in other refereed publications; or a description of successful methods of techniques of education, outreach, or technology transfer.