Comparison of the edge detection methods to detect, identify and locate the obstacles for agricultural robotic vehicles
| dc.contributor.author | Mahdi, Anas Qasim | |
| dc.date.accessioned | 2014-10-09T11:17:04Z | |
| dc.date.available | 2014-10-09T11:17:04Z | |
| dc.date.issued | 2014-01 | |
| dc.description | Master of Science in Computer Engineering. Thesis (M.S.)--Eastern Mediterranean University, Faculty of Engineering, Dept. of Computer Engineering, 2014. Supervisor: Assist. Prof. Dr. Mehmet Bodur. | en_US |
| dc.description.abstract | ABSTRACT: The obstacle detection in an agricultural field is an important step of the automation of the plantation. There are already developed autonomous agricultural vehicles that can track a path, and perform the specified processes on the plantation fields. These autonomous agricultural robotic machines need an upper level of control, which is mostly performed manually, for the design of the reference paths. Detection of the agricultural obstacles is necessary to accomplish these manual tasks in an automatic manner. In this study, statistical methods are employed to determine which of the five well-known edge-detection methods is best, for the high-level path planning in an agricultural automation of autonomous agricultural vehicles depending on field and image properties. Keywords: agricultural robotic, edge detection techniques, Canny, Prewitt, Robert, Sobel, obstacle detection. ………………………………………………………………………………………………………………………………………………………………………………………………………… ÖZ:Tarım alanlarında engel tesbiti tarımsal otomasyonu önemli bir basamağıdır. Tarım arazilerinde verilen bir yolu takip ederek belirtilen işlemleri uygulamak üzere geliştirilmiş tarım aracları şimdiden mevcuttur. Bu otonom tarım robotları şimdilik elle gerçekleştirilen üst düzeyde bir yol tasarımına gerek duyarlar. İşin tümüyle otomasyonu için tarımsal engellerin tesbitini otomatik olarak yapabilmek gerekir. Bu çalışmada, tarımsal üst düzey yol planlaması açısından en iyi kenar belirleme yöntemi araştırılmış, istatistiksel yöntemler ile yaygın bilinen beş yöntemin arazi ve resim özelliklerine bağlı olarak hangisinin iyi sonuç verdiği belirlenmiştir. | en_US |
| dc.identifier.citation | Mahdi, Anas Qasim. (2014). Comparison of the edge detection methods to detect, identify and locate the obstacles for agricultural robotic vehicles. Thesis (M.S.), Eastern Mediterranean University, Institute of Graduate Studies and Research, Dept. of Computer Engineering, Famagusta: North Cyprus. | en_US |
| dc.identifier.uri | https://hdl.handle.net/11129/1404 | |
| dc.language.iso | en | |
| dc.publisher | Eastern Mediterranean University (EMU) - Doğu Akdeniz Üniversitesi (DAÜ) | en_US |
| dc.relation.publicationcategory | Tez | |
| dc.subject | Computer Engineering | en_US |
| dc.subject | Architecture - Vehicles, Robotic | en_US |
| dc.subject | Agricultural Robotic, Edge Detection Techniques, Canny, Prewitt, Robert, Sobel, Obstacle Detection | en_US |
| dc.title | Comparison of the edge detection methods to detect, identify and locate the obstacles for agricultural robotic vehicles | en_US |
| dc.type | Thesis |
