An automatic landmarking algorithm for leaf morphology based on conformal mapping

• An automatic landmarking algorithm was proposed to extract homologous landmark coordinates to describe leaf shape. • Leaf outline can be transformed into a monotonically increasing function to simplify the leaf morphology features. • Computer graphics algorithms can be introduced to achieve shape features matching between different leaves. • The algorithm was verified to work well across leaf datasets of different varieties and different growth stages. Leaf shape is of great significance in plant phenotype research. Landmarks method is a widely used morphometric approach, which can comprehensively describe the morphological differences among leaves. However, the selection of landmarks is time-consuming and laborious. An automatic landmarking algorithm is proposed here. Based on conformal mapping, the leaf outline can be transformed into a monotonically increasing function curve, referred to as the ’fingerprint function’. The Dynamic Time Warping (DTW) algorithm was introduced to match landmarks between different leaves. Two leaf datasets were used to validate the algorithm separately in different species and developmental stages. Dataset1 is a public dataset which covers 26 different types of leaves. The average positional difference between automatic and manual landmarks for dataset1 was only 2.95%. Dataset2 consists of cotton leaves collected in the field at various growth stages, and the positional difference for this dataset was all below 5%. These results validate that our algorithm is applicable to a wide range of leaf types and capable of identifying and locating novel features that emerge during leaf growth. The automatic landmarking algorithm can simulate manual landmarking to a great extent. It provides a new approach for automated acquisition of plant leaf shape homology tailored to the research needs of botanists.

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Publication Details

Journal
Computers and Electronics in Agriculture
Published
2025-03-17
DOI
https://doi.org/10.1016/j.compag.2025.110274
Citations
1
Primary Topic
Morphological variations and asymmetry
Type
article
Field-Weighted Citation Impact
4.09
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article

An automatic landmarking algorithm for leaf morphology based on conformal mapping

Xiaojun Liu, Yanyong Guo, Hu Zhou, Yulu Ye et al.
1 citations
Computers and Electronics in Agriculture
Morphological variations and asymmetry
4.09
article

An automatic landmarking algorithm for leaf morphology based on conformal mapping

Xiaojun Liu, Yanyong Guo, Hu Zhou, Yulu Ye, Yuntao Ma, Rui Zhang, Baoguo Li, Junjie Zhu, Peige Zhong
article en
1 citations

Abstract

• An automatic landmarking algorithm was proposed to extract homologous landmark coordinates to describe leaf shape. • Leaf outline can be transformed into a monotonically increasing function to simplify the leaf morphology features. • Computer graphics algorithms can be introduced to achieve shape features matching between different leaves. • The algorithm was verified to work well across leaf datasets of different varieties and different growth stages. Leaf shape is of great significance in plant phenotype research. Landmarks method is a widely used morphometric approach, which can comprehensively describe the morphological differences among leaves. However, the selection of landmarks is time-consuming and laborious. An automatic landmarking algorithm is proposed here. Based on conformal mapping, the leaf outline can be transformed into a monotonically increasing function curve, referred to as the ’fingerprint function’. The Dynamic Time Warping (DTW) algorithm was introduced to match landmarks between different leaves. Two leaf datasets were used to validate the algorithm separately in different species and developmental stages. Dataset1 is a public dataset which covers 26 different types of leaves. The average positional difference between automatic and manual landmarks for dataset1 was only 2.95%. Dataset2 consists of cotton leaves collected in the field at various growth stages, and the positional difference for this dataset was all below 5%. These results validate that our algorithm is applicable to a wide range of leaf types and capable of identifying and locating novel features that emerge during leaf growth. The automatic landmarking algorithm can simulate manual landmarking to a great extent. It provides a new approach for automated acquisition of plant leaf shape homology tailored to the research needs of botanists.

Computers and Electronics in AgricultureVol. 234
Institute of Vegetables and Flowers (CN), Chinese Academy of Agricultural Sciences (CN), Biotechnology Research Institute (CN), China Agricultural University (CN)
Sustainable cities and communities
Openalex Percentile: Top 12%
Morphological variations and asymmetry
4.09
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