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Photometric stereo for three-dimensional leaf venation extraction

Zhang, Wenhao; Hansen, Mark F; Smith, Melvyn; Smith, Lyndon; Grieve, Bruce


Wenhao Zhang
Senior Lecturer in Machine Vision

Mark Hansen
Associate Professor in Knowledge Exchange & External Engagement

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Melvyn Smith
Research Centre Director Vision Lab/Prof

Lyndon Smith
Professor in Computer Simulation and Machine

Bruce Grieve


© 2018 Elsevier B.V. Leaf venation extraction studies have been strongly discouraged by considerable challenges posed by venation architectures that are complex, diverse and subtle. Additionally, unpredictable local leaf curvatures, undesirable ambient illuminations, and abnormal conditions of leaves may coexist with other complications. While leaf venation extraction has high potential for assisting with plant phenotyping, speciation and modelling, its investigations to date have been confined to colour image acquisition and processing which are commonly confounded by the aforementioned biotic and abiotic variations. To bridge the gaps in this area, we have designed a 3D imaging system for leaf venation extraction, which can overcome dark or bright ambient illumination and can allow for 3D data reconstruction in high resolution. We further propose a novel leaf venation extraction algorithm that can obtain illumination-independent surface normal features by performing Photometric Stereo reconstruction as well as local shape measures by fusing the decoupled shape index and curvedness features. In addition, this algorithm can determine venation polarity – whether veins are raised above or recessed into a leaf. Tests on both sides of different leaf species with varied venation architectures show that the proposed method is accurate in extracting the primary, secondary and even tertiary veins. It also proves to be robust against leaf diseases which can cause dramatic changes in colour. The effectiveness of this algorithm in determining venation polarity is verified by it correctly recognising raised or recessed veins in nine different experiments.


Zhang, W., Hansen, M. F., Smith, M., Smith, L., & Grieve, B. (2018). Photometric stereo for three-dimensional leaf venation extraction. Computers in Industry, 98, 56-67.

Journal Article Type Article
Acceptance Date Feb 22, 2018
Online Publication Date Mar 8, 2018
Publication Date Jun 1, 2018
Deposit Date Mar 12, 2018
Publicly Available Date Jan 10, 2020
Journal Computers in Industry
Print ISSN 0166-3615
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 98
Pages 56-67
Keywords leaf venation, leaf disease, 3D imaging, shape index, photometric stereo, ridge detection
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