Xychryz A-ron P. Calangian, J. Gonzales, Crizel Aile N. Hilario, J. M. López, Boyd Lemuel E. Rulona, Immanuel Jose C. Valencia, R. Billones, Pocholo James M. Loresco, I. Valenzuela, E. Dadios
{"title":"基于视觉的冠层面积测量","authors":"Xychryz A-ron P. Calangian, J. Gonzales, Crizel Aile N. Hilario, J. M. López, Boyd Lemuel E. Rulona, Immanuel Jose C. Valencia, R. Billones, Pocholo James M. Loresco, I. Valenzuela, E. Dadios","doi":"10.1109/HNICEM.2018.8666251","DOIUrl":null,"url":null,"abstract":"Canopy area measurement is one of the important crop growth factors that is considered for the crop yield. This has been widely used parameter all over the world. Yet, the development of a system that can automatically computes the canopy area of the crop is still a challenge. In this study, a vision-based system is proposed. The system captures the image of the crop and process this through image processing algorithm. The extracted feature of the image is the pixel count. This pixel count determines the canopy area of the crop. A mathematical model was developed for the approximation of the canopy area.","PeriodicalId":426103,"journal":{"name":"2018 IEEE 10th International Conference on Humanoid, Nanotechnology, Information Technology,Communication and Control, Environment and Management (HNICEM)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"Vision-based Canopy Area Measurements\",\"authors\":\"Xychryz A-ron P. Calangian, J. Gonzales, Crizel Aile N. Hilario, J. M. López, Boyd Lemuel E. Rulona, Immanuel Jose C. Valencia, R. Billones, Pocholo James M. Loresco, I. Valenzuela, E. Dadios\",\"doi\":\"10.1109/HNICEM.2018.8666251\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Canopy area measurement is one of the important crop growth factors that is considered for the crop yield. This has been widely used parameter all over the world. Yet, the development of a system that can automatically computes the canopy area of the crop is still a challenge. In this study, a vision-based system is proposed. The system captures the image of the crop and process this through image processing algorithm. The extracted feature of the image is the pixel count. This pixel count determines the canopy area of the crop. A mathematical model was developed for the approximation of the canopy area.\",\"PeriodicalId\":426103,\"journal\":{\"name\":\"2018 IEEE 10th International Conference on Humanoid, Nanotechnology, Information Technology,Communication and Control, Environment and Management (HNICEM)\",\"volume\":\"53 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE 10th International Conference on Humanoid, Nanotechnology, Information Technology,Communication and Control, Environment and Management (HNICEM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HNICEM.2018.8666251\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 10th International Conference on Humanoid, Nanotechnology, Information Technology,Communication and Control, Environment and Management (HNICEM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HNICEM.2018.8666251","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Canopy area measurement is one of the important crop growth factors that is considered for the crop yield. This has been widely used parameter all over the world. Yet, the development of a system that can automatically computes the canopy area of the crop is still a challenge. In this study, a vision-based system is proposed. The system captures the image of the crop and process this through image processing algorithm. The extracted feature of the image is the pixel count. This pixel count determines the canopy area of the crop. A mathematical model was developed for the approximation of the canopy area.