Cut-Edge Detection Method for Rice Harvesting Based on Machine Vision
نویسندگان
چکیده
منابع مشابه
An Adaptive Fuzzy Crop Edge Detection Method for Machine Vision
1Graduate Fellow, Department of Agricultural Engineering, University of Illinois at Urbana Champaign, IL, USA. 2Professor, Department of Agricultural Engineering, University of Illinois at Urbana Champaign, IL, USA. 3Assistant Professor, Department of Agricultural Engineering, University of Illinois at Urbana Champaign, IL, USA. 4Professor, Departamento de Engenharia Agrícola, Universidade Fede...
متن کاملDetection of Rice Exterior Quality based on Machine Vision
To investigate the detection of rice exterior quality, a machine vision system was developed. The main characteristics of rice appearance including area, perimeter, roughness and minimum enclosing rectangle were calculated by image analysis. Least Squares Support Vector Machines, Naive Bayes Classifier and Back Propagation Artificial Neural Network were applied to achieve classification of head...
متن کاملGlass Product Defects Detection Method Based on Machine Vision
This paper develops the machine vision based detection method to detect glass products defects. The novel segmentation method based on unsupervised learning is proposed to segment the defect regions and background. The fuzzy support vector machine was adopted as classifiers for the extracted features. The experimental results indicated the accuracy rate can reach up to 96.7 % by using the metho...
متن کاملMachine Vision Based Cotton Recognition for Cotton Harvesting Robot
A new cotton recognition method is proposed in this paper. It provides parameters for motion of the manipulator so that it can acquire precise location information of cotton, identify cotton from surroundings correctly, and accordingly pick up them automatically. This method is based on color subtraction information of different parts of cotton. Furthermore, in order to increase accuracy rate o...
متن کاملMachine Vision Based Classification Of Tobacco Leaves For Automatic Harvesting
A machine vision based approach for classification of tobacco leaves for automatic harvesting in a complex agricultural environment is proposed in this paper. The CIELAB color space model is used to segment the leaf from the background. The segmented leaves are classified into three classes viz., ripe, unripe, and over-ripe. Models based on various textural features such as GLTP (Gray Level Loc...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Agronomy
سال: 2020
ISSN: 2073-4395
DOI: 10.3390/agronomy10040590