Plant Leaf Classification Using Color on a Gravitational Approach

2013 ◽  
pp. 258-265 ◽  
Author(s):  
Jarbas J. de M. Sá Junior ◽  
André R. Backes ◽  
Paulo César Cortez
Keyword(s):  
Plant Leaf

Relational analysis of spectra and red-edge characteristics of plant leaf and leaf biochemical constituent

2010 ◽  
Vol 18 (4) ◽  
pp. 804-809 ◽  
Author(s):  
Shou-Zhen LIANG ◽  
Ping SHI ◽  
Wan-Dong MA ◽  
Qian-Guo XING ◽  
Liang-Ju YU
Keyword(s):  
Plant Leaf ◽  
Relational Analysis ◽  
Red Edge ◽  
Biochemical Constituent

CLEAN CUTICLE OR CLEARED LEAF – FOSSIL PLANT LEAF PREPARATION METHODS FOR PCO2 RECONSTRUCTION

2020 ◽  
Author(s):  
Jiaqi Liang ◽  
◽  
Kevin Burke ◽  
Liang Xiao ◽  
Qin Leng ◽  
...  
Keyword(s):  
Fossil Plant ◽  
Preparation Methods ◽  
Plant Leaf

Classification and Recognition of Plant Leaf Based on Neural Networks

2011 ◽  
Vol 464 ◽  
pp. 38-42 ◽  
Author(s):  
Ping Ye ◽  
Gui Rong Weng
Keyword(s):  
Neural Networks ◽  
Fractal Dimension ◽  
Recognition Rate ◽  
Image Binarization ◽  
Characteristic Parameters ◽  
Moment Invariant ◽  
Plant Leaf ◽  
The Neural Networks ◽  
Novel Method ◽  
The Moment

This paper proposed a novel method for leaf classification and recognition. In the method, the moment invariant and fractal dimension were regarded as the characteristic parameters of the plant leaf. In order to extract the representative characteristic parameters, pretreatment of the leaf images, including RGB-gray converting, image binarization and leafstalk removing. The extracted leaf characteristic parameters were further utilized as training sets to train the neural networks. The proposed method was proved effectively to reach a recognition rate about 92% for most of the testing leaf samples

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