Plant species identification using Elliptic Fourier leaf shape analysis

By J. C. Neto, George E. Meyer, David D. Jones, A. Samal. 2006

327 citations recorded by the source corpus.

How researchers see this paper

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Plant species identification using digital morphometrics: A review (2012, methodology): “We now discuss a number of approaches to leaf shape analysis, including Fourier analysis, contour signatures, landmark analysis, shape features, fractal dimensions and texture analysis.”
The ImageCLEF 2012 Plant Identification Task (2012, unknown): “…frequently used class of methods is shape boundary analysis (16 runs among 30 used), exclusively or not) which is not surprising since state-of-the-art methods addressing leaf-based identiﬁcation in the literature are mostly based on leaf segmentation and shape boundary features [7, 18, 9, 23, 5].”
How deep learning extracts and learns leaf features for plant classification (2017, methodology): “[11] introduced Elliptic Fourier and discriminant analyses to distinguish different plant species based on their leaf shape.”
Evaluation of variations in the shape of grain types using principal components analysis of the elliptic Fourier descriptors (2012, methodology): “The elliptic Fourier series approximation of closed contour projected on the x and y-axes can be defined as follows (Neto et al., 2006; Hiraoka and Kuramoto, 2004; Mebatsion and Paliwal, 2011):”
Verification of color vegetation indices for automated crop imaging applications (2008, methodology): “A third step was to apply the Elliptic Fourier shape feature analysis to each extracted leaf (Camargo Neto et al., 2006b).”