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LeafLoDs: A Self-Adaptive 3-D leaf modeling with enhancing level of details expression.

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Title: LeafLoDs: A Self-Adaptive 3-D leaf modeling with enhancing level of details expression.
Authors: Hui, Zhenyang1,2,3 (AUTHOR) huizhenyang2008@ecut.edu.cn, He, Yating1,2,3 (AUTHOR) 2022120403@ecut.edu.cn, Jin, Shuanggen4,5 (AUTHOR) sgjin@shao.ac.cn, Chen, Wenbo1,2,3 (AUTHOR) 202260010@ecut.edu.cn, He, Haiqing1,2,3 (AUTHOR) hehaiqing@ecut.edu.cn, Ziggah, Yao Yevenyo6 (AUTHOR) yyziggah@umat.edu.gh
Source: Computers & Electronics in Agriculture. Mar2026, Vol. 243, pN.PAG-N.PAG. 1p.
Subjects: Three-dimensional modeling, Morphology, Leaf anatomy, Abstraction (Computer science), Foliar diagnosis, Plant development
Abstract: • A robust 3D leaf modelling method based on multi-level veins is proposed. • Multi-level veins are generated by leveraging morphological leaf traits. • Different LoDs are achieved by incorporating varying degrees of vein structures. Leaves play a crucial role in the growth of plants, both functionally and structurally. To meet the requirements of various levels of detail (LoDs) in leaf modeling for different applications, this paper introduces a self-adaptive 3D leaf modeling method aimed at enhancing LoDs representation. In this paper, a self-adaptive leaf axis determination method is first presented. According to the built leaf axis, feature points including contour points, inner corners, and outer corners are identified. Subsequently, based on these feature points, a multi-level veins generation model is proposed, extracting primary, secondary, and tertiary veins individually by leveraging the geometric and morphological traits of the leaf through a spatial colonization strategy. Hereafter, the three-dimensional leaf modeling achieves different LoDs by incorporating varying degrees of vein structures. To evaluate the effectiveness of the proposed method, both simulated and real datasets are utilized for testing. The simulated datasets consist of leaves from four different types, such as entire, toothed, disercted and digitate demonstrating that the method produces satisfactory results with small area deviation and distance residuals. In the real datasets, seven individual tomatoes with a total of 228 leaves are tested, showing that the proposed modeling approach aligns effectively with real data, with distance residuals mostly falling within -0.4 cm to 0.4 cm from real point clouds. Experimental results also reveal that higher levels of modeling lead to better outcomes due to increased detail from additional veins and feature points incorporated in the modeling process. [ABSTRACT FROM AUTHOR]
Copyright of Computers & Electronics in Agriculture is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 191266145
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PubType: Academic Journal
PubTypeId: academicJournal
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  Data: LeafLoDs: A Self-Adaptive 3-D leaf modeling with enhancing level of details expression.
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  Data: <searchLink fieldCode="AR" term="%22Hui%2C+Zhenyang%22">Hui, Zhenyang</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR)<i> huizhenyang2008@ecut.edu.cn</i><br /><searchLink fieldCode="AR" term="%22He%2C+Yating%22">He, Yating</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR)<i> 2022120403@ecut.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Jin%2C+Shuanggen%22">Jin, Shuanggen</searchLink><relatesTo>4,5</relatesTo> (AUTHOR)<i> sgjin@shao.ac.cn</i><br /><searchLink fieldCode="AR" term="%22Chen%2C+Wenbo%22">Chen, Wenbo</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR)<i> 202260010@ecut.edu.cn</i><br /><searchLink fieldCode="AR" term="%22He%2C+Haiqing%22">He, Haiqing</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR)<i> hehaiqing@ecut.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Ziggah%2C+Yao+Yevenyo%22">Ziggah, Yao Yevenyo</searchLink><relatesTo>6</relatesTo> (AUTHOR)<i> yyziggah@umat.edu.gh</i>
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  Data: <searchLink fieldCode="JN" term="%22Computers+%26+Electronics+in+Agriculture%22">Computers & Electronics in Agriculture</searchLink>. Mar2026, Vol. 243, pN.PAG-N.PAG. 1p.
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  Data: <searchLink fieldCode="DE" term="%22Three-dimensional+modeling%22">Three-dimensional modeling</searchLink><br /><searchLink fieldCode="DE" term="%22Morphology%22">Morphology</searchLink><br /><searchLink fieldCode="DE" term="%22Leaf+anatomy%22">Leaf anatomy</searchLink><br /><searchLink fieldCode="DE" term="%22Abstraction+%28Computer+science%29%22">Abstraction (Computer science)</searchLink><br /><searchLink fieldCode="DE" term="%22Foliar+diagnosis%22">Foliar diagnosis</searchLink><br /><searchLink fieldCode="DE" term="%22Plant+development%22">Plant development</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: • A robust 3D leaf modelling method based on multi-level veins is proposed. • Multi-level veins are generated by leveraging morphological leaf traits. • Different LoDs are achieved by incorporating varying degrees of vein structures. Leaves play a crucial role in the growth of plants, both functionally and structurally. To meet the requirements of various levels of detail (LoDs) in leaf modeling for different applications, this paper introduces a self-adaptive 3D leaf modeling method aimed at enhancing LoDs representation. In this paper, a self-adaptive leaf axis determination method is first presented. According to the built leaf axis, feature points including contour points, inner corners, and outer corners are identified. Subsequently, based on these feature points, a multi-level veins generation model is proposed, extracting primary, secondary, and tertiary veins individually by leveraging the geometric and morphological traits of the leaf through a spatial colonization strategy. Hereafter, the three-dimensional leaf modeling achieves different LoDs by incorporating varying degrees of vein structures. To evaluate the effectiveness of the proposed method, both simulated and real datasets are utilized for testing. The simulated datasets consist of leaves from four different types, such as entire, toothed, disercted and digitate demonstrating that the method produces satisfactory results with small area deviation and distance residuals. In the real datasets, seven individual tomatoes with a total of 228 leaves are tested, showing that the proposed modeling approach aligns effectively with real data, with distance residuals mostly falling within -0.4 cm to 0.4 cm from real point clouds. Experimental results also reveal that higher levels of modeling lead to better outcomes due to increased detail from additional veins and feature points incorporated in the modeling process. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Computers & Electronics in Agriculture is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1016/j.compag.2025.111377
    Languages:
      – Code: eng
        Text: English
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      Pagination:
        PageCount: 1
        StartPage: N.PAG
    Subjects:
      – SubjectFull: Three-dimensional modeling
        Type: general
      – SubjectFull: Morphology
        Type: general
      – SubjectFull: Leaf anatomy
        Type: general
      – SubjectFull: Abstraction (Computer science)
        Type: general
      – SubjectFull: Foliar diagnosis
        Type: general
      – SubjectFull: Plant development
        Type: general
    Titles:
      – TitleFull: LeafLoDs: A Self-Adaptive 3-D leaf modeling with enhancing level of details expression.
        Type: main
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          Name:
            NameFull: Hui, Zhenyang
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            NameFull: He, Yating
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            NameFull: Jin, Shuanggen
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            NameFull: Chen, Wenbo
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            NameFull: He, Haiqing
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            NameFull: Ziggah, Yao Yevenyo
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          Dates:
            – D: 01
              M: 03
              Text: Mar2026
              Type: published
              Y: 2026
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              Value: 01681699
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              Value: 243
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            – TitleFull: Computers & Electronics in Agriculture
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