@article{
 title = {A leaf vein detection scheme for locating individual plant leaves},
 type = {article},
 year = {2018},
 keywords = {leaf pose,leaf recognition,leaf segmentation,leaf skeleton},
 month = {11},
 publisher = {Institute of Electrical and Electronics Engineers Inc.},
 day = {27},
 id = {311a18c5-8747-35c0-8e5e-e4b9c4700500},
 created = {2024-01-29T15:18:33.249Z},
 accessed = {2024-01-29},
 file_attached = {true},
 profile_id = {f1f70cad-e32d-3de2-a3c0-be1736cb88be},
 group_id = {5ec9cc91-a5d6-3de5-82f3-3ef3d98a89c1},
 last_modified = {2024-01-29T15:18:42.720Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 folder_uuids = {5a010301-acb6-4642-a6b2-8afaee1b741c},
 private_publication = {false},
 abstract = {Individual leaf detection from natural condition is a fundamental task for many agricultural automation systems. Individual leaf detection is challenging because of the complicity of shape variation and pose changing of living plant leaves. In this paper, we proposed a leaf detection scheme by examining leaf veins. Individual leaves could be located in the plant images and their direction could be estimated. Initially, background is removed by examining luminance and smoothness in G channel of RGB color space. Accordingly, a SKEDET method is proposed to extract candidate skeleton of leaves. The longest skeleton of a leaf is selected as the main leaf vein. Subsequently, the direction of leaf is estimated according to thickness of the vein. The experiments were carried out with sweet potato leaves. The experimental results demonstrated that the proposed method could stably detect individual leaves and their directions. The proposed method could be applied to many agricultural applications, such as plant inspection system, agricultural robotics.},
 bibtype = {article},
 author = {Zhang, Liankuan and Xia, Chunlei and Xiao, Deqin and Weckler, Paul and Lan, Yubin and Lee, Jang Myung},
 doi = {10.1109/ICT-ROBOT.2018.8549901},
 journal = {2018 International Conference on Information and Communication Technology Robotics, ICT-ROBOT 2018}
}

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Individual leaf detection is challenging because of the complicity of shape variation and pose changing of living plant leaves. In this paper, we proposed a leaf detection scheme by examining leaf veins. Individual leaves could be located in the plant images and their direction could be estimated. Initially, background is removed by examining luminance and smoothness in G channel of RGB color space. Accordingly, a SKEDET method is proposed to extract candidate skeleton of leaves. The longest skeleton of a leaf is selected as the main leaf vein. Subsequently, the direction of leaf is estimated according to thickness of the vein. The experiments were carried out with sweet potato leaves. The experimental results demonstrated that the proposed method could stably detect individual leaves and their directions. The proposed method could be applied to many agricultural applications, such as plant inspection system, agricultural robotics.","bibtype":"article","author":"Zhang, Liankuan and Xia, Chunlei and Xiao, Deqin and Weckler, Paul and Lan, Yubin and Lee, Jang Myung","doi":"10.1109/ICT-ROBOT.2018.8549901","journal":"2018 International Conference on Information and Communication Technology Robotics, ICT-ROBOT 2018","bibtex":"@article{\n title = {A leaf vein detection scheme for locating individual plant leaves},\n type = {article},\n year = {2018},\n keywords = {leaf pose,leaf recognition,leaf segmentation,leaf skeleton},\n month = {11},\n publisher = {Institute of Electrical and Electronics Engineers Inc.},\n day = {27},\n id = {311a18c5-8747-35c0-8e5e-e4b9c4700500},\n created = {2024-01-29T15:18:33.249Z},\n accessed = {2024-01-29},\n file_attached = {true},\n profile_id = {f1f70cad-e32d-3de2-a3c0-be1736cb88be},\n group_id = {5ec9cc91-a5d6-3de5-82f3-3ef3d98a89c1},\n last_modified = {2024-01-29T15:18:42.720Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n folder_uuids = {5a010301-acb6-4642-a6b2-8afaee1b741c},\n private_publication = {false},\n abstract = {Individual leaf detection from natural condition is a fundamental task for many agricultural automation systems. Individual leaf detection is challenging because of the complicity of shape variation and pose changing of living plant leaves. In this paper, we proposed a leaf detection scheme by examining leaf veins. Individual leaves could be located in the plant images and their direction could be estimated. Initially, background is removed by examining luminance and smoothness in G channel of RGB color space. Accordingly, a SKEDET method is proposed to extract candidate skeleton of leaves. The longest skeleton of a leaf is selected as the main leaf vein. Subsequently, the direction of leaf is estimated according to thickness of the vein. The experiments were carried out with sweet potato leaves. The experimental results demonstrated that the proposed method could stably detect individual leaves and their directions. 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