Abstract
Rapidly determining leaf vein network patterns and vein densities is biologically important and technically challenging. Current methods, however, are limited to vein contour extraction. Further image processing is difficult, and some leaf vein traits of interest therefore cannot be quantified. In this study, we proposed a novel method for the fast and accurate determination of leaf vein network patterns and vein density. Nine tree species with different leaf characteristics and vein types were applied to verify this method. To overcome the image processing difficulties at the microscopic scale, we adopted the remote object-oriented classification method applied comprehensively in the field of remote sensing research. The key to this approach is to determine the universally applicable leaf vein extraction threshold values (scale parameter, shape parameter, compactness parameter, brightness feature, spectral feature and geometric feature). Based on our analysis, the following recommended threshold values were determined: the scale parameter was 250, the shape parameter was 0.7, the compactness parameter was 0.3, the brightness feature value was 230∼280, the spectral feature value was 180∼230, and the geometric feature value was less than 2. With the optimal extraction parameters applied, the extraction precision was above 96.40% on average for the nine species studied. The leaf vein density calculation rate increased by more than 87.3% compared to that of the traditional methods. The results showed that this method is accurate, fast, flexible and complementary to existing technologies. It is an effective tool for the fast extraction of vein networks and the exploration of leaf vein characteristics, particularly for large-scale studies in plant vein physiology.
Highlights
The leaf vein network, an important morphological structure, is widely distributed on the leaf surface
Fast Method for Vein Extraction extraction of leaf veins by different scale parameters (P ≤ 0.05), but there were no significant differences among different tree species (P > 0.05)
We proposed a novel method for the fast and accurate determination of leaf vein network patterns and vein density
Summary
The leaf vein network, an important morphological structure, is widely distributed on the leaf surface. It affects the mechanical support, water balance and resource circulation of the entire leaf (Wright et al, 2004; Brodribb and Holbrook, 2005; Lavorel and Grigulis, 2015; Cai et al, 2018). One important trait of the network is vein density, the total length of the leaf vein per unit area, which
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