{"title":"使用生产和外国消防部门的立体视觉系统定义工厂高度","authors":"Ö. Özlüoymak","doi":"10.33462/jotaf.626709","DOIUrl":null,"url":null,"abstract":"The stereo vision experiments were conducted under the laboratory conditions by using LabVIEW programming language. An artificial crop plant and six types of artificial weed samples were used in the experiments. The information related to the plant height is a relevant feature to classify the crop plant and weed, especially in the early growth stage. A binocular stereo vision system was established by using two identical webcams with parallel optical axes and a laptop computer to discriminate the artificial crop plant and six types of weeds correctly. The calculated depth values were compared with the physical measurements for the same points. While the measurement error of the system was less than 3.50% for the artificial crop plant, it was less than 4.20% for six artificial weed samples. There were also strong, positive and significant linear correlations between the stereo vision and physical height measurements for artificial crop plant and weed samples. Calculated correlation values (R 2 ) between the stereo vision and physical height measurements were 0.962 for the artificial crop plant and 0.978 for the artificial weed samples, respectively. That stereo vision system could be integrated into automatic spraying systems for intra-row spraying applications.","PeriodicalId":44038,"journal":{"name":"Journal of Tekirdag Agriculture Faculty-Tekirdag Ziraat Fakultesi Dergisi","volume":null,"pages":null},"PeriodicalIF":0.6000,"publicationDate":"2020-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Ürün ve Yabancı Ot Ayrımı için Stereo Görme Sistemi Kullanılarak Bitki Yüksekliğinin Belirlenmesi\",\"authors\":\"Ö. Özlüoymak\",\"doi\":\"10.33462/jotaf.626709\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The stereo vision experiments were conducted under the laboratory conditions by using LabVIEW programming language. An artificial crop plant and six types of artificial weed samples were used in the experiments. The information related to the plant height is a relevant feature to classify the crop plant and weed, especially in the early growth stage. A binocular stereo vision system was established by using two identical webcams with parallel optical axes and a laptop computer to discriminate the artificial crop plant and six types of weeds correctly. The calculated depth values were compared with the physical measurements for the same points. While the measurement error of the system was less than 3.50% for the artificial crop plant, it was less than 4.20% for six artificial weed samples. There were also strong, positive and significant linear correlations between the stereo vision and physical height measurements for artificial crop plant and weed samples. Calculated correlation values (R 2 ) between the stereo vision and physical height measurements were 0.962 for the artificial crop plant and 0.978 for the artificial weed samples, respectively. That stereo vision system could be integrated into automatic spraying systems for intra-row spraying applications.\",\"PeriodicalId\":44038,\"journal\":{\"name\":\"Journal of Tekirdag Agriculture Faculty-Tekirdag Ziraat Fakultesi Dergisi\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2020-01-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Tekirdag Agriculture Faculty-Tekirdag Ziraat Fakultesi Dergisi\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.33462/jotaf.626709\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"AGRICULTURE, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Tekirdag Agriculture Faculty-Tekirdag Ziraat Fakultesi Dergisi","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33462/jotaf.626709","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"AGRICULTURE, MULTIDISCIPLINARY","Score":null,"Total":0}
Ürün ve Yabancı Ot Ayrımı için Stereo Görme Sistemi Kullanılarak Bitki Yüksekliğinin Belirlenmesi
The stereo vision experiments were conducted under the laboratory conditions by using LabVIEW programming language. An artificial crop plant and six types of artificial weed samples were used in the experiments. The information related to the plant height is a relevant feature to classify the crop plant and weed, especially in the early growth stage. A binocular stereo vision system was established by using two identical webcams with parallel optical axes and a laptop computer to discriminate the artificial crop plant and six types of weeds correctly. The calculated depth values were compared with the physical measurements for the same points. While the measurement error of the system was less than 3.50% for the artificial crop plant, it was less than 4.20% for six artificial weed samples. There were also strong, positive and significant linear correlations between the stereo vision and physical height measurements for artificial crop plant and weed samples. Calculated correlation values (R 2 ) between the stereo vision and physical height measurements were 0.962 for the artificial crop plant and 0.978 for the artificial weed samples, respectively. That stereo vision system could be integrated into automatic spraying systems for intra-row spraying applications.
期刊介绍:
Journal of Tekirdag Agricultural Faculty (JOTAF) is an international peer-reviewed journal publishing at least three issues a year (January, May and September). New and original research papers on all of agriculture-including agricultural economics, agricultural machinery, irrigation and drainage, animal sciences, food engineering, field crops, horticulture, plant protection, biosystem engineering and soil science are considered for publishing as hard copy and electronic copy. The papers are published in English and Turkish languages. The journal will consider submissions related to agricultural sciences from all over the world and submissions that were published or submitted for publication to any other journals will be not accepted. JOTAF is published by the University of Namik Kemal, Faculty of Agricultural.