Abstract:
In this paper we propose a method to segment individual leaves of crop plants from Unmanned Aerial Vehicle (UAV) imagery for the purposes of deriving phenotypic propertie...Show MoreMetadata
Abstract:
In this paper we propose a method to segment individual leaves of crop plants from Unmanned Aerial Vehicle (UAV) imagery for the purposes of deriving phenotypic properties of the plant. The crop plant used in our study is sorghum [Sorghum bicolor (L.) Moench]. Phenotyping is a set of methodologies for analyzing and obtaining characteristic traits of a plant. In a phenotypic study, leaves are often used to estimate traits such as individual leaf area and Leaf Area Index (LAI). Our approach is to segment the leaves in polar coordinates using the plant center as the origin. The shape of each leaf is estimated by a shape model. Experimental results indicate that this approach can provide good estimates of leaf phenotypic properties.
Date of Conference: 17-20 September 2017
Date Added to IEEE Xplore: 22 February 2018
ISBN Information:
Electronic ISSN: 2381-8549
Identification of Soybean Foliar Diseases Using Unmanned Aerial Vehicle Images
Everton Castelão Tetila,Bruno Brandoli Machado,Nícolas Alessandro Belete,David Augusto Guimarães,Hemerson Pistori
Road Segmentation of Unmanned Aerial Vehicle Remote Sensing Images Using Adversarial Network With Multiscale Context Aggregation
Yuxia Li,Bo Peng,Lei He,Kunlong Fan,Ling Tong
Unmanned Aerial Vehicle remote sensing image dehazing via global parameters
Yufeng Fan,Yongfeng Cao,Xiuzhang Yang
Automatic dragon fruit counting using adaptive thresholds for image segmentation and shape analysis
Chi Cuong Tran,Dinh Tu Nguyen,Hoang Dang Le,Quoc Bao Truong,Quoc Dinh Truong
Index-guided natural image segmentation
Dongxiang Chi,Ming Li,Ying Zhao,Jing Hu
Segmentation of Low-Cost Remote Sensing Images Combining Vegetation Indices and Mean Shift
Moacir P. Ponti
Semantic segmentation of vegetation images acquired by unmanned aerial vehicles using an ensemble of ConvNets
Keiller Nogueira,Jefersson A. dos Santos,Leonardo Cancian,Bruno D. Borges,Thiago S. F. Silva,Leonor Patricia Morellato,Ricardo da S. Torres
Study of an Index for Assessing Grass Quality in Pastures Using RGB Images Obtained by Unmanned Aerial Vehicle
Teodora Petrova,Marin Marinov,Zhivo Petrov
Adapting artificial hopfield neural network for agriculture satellite image segmentation
Rachid Sammouda,Ameur Touir,Yaser A. Reyad,Nuru Adgaba,Ahmed Ai-Ghamdi,Said Saad Hegazy