Open Access
ARTICLE
CNN Approaches for Classification of Indian Leaf Species Using Smartphones
M. Vilasini1, *, P. Ramamoorthy2
1 KPR Institute of Engineering and Technology, Coimbatore, 641407, India.
2 Adithiya Institute of Engineering and Technology, Coimbatore, 641107, India.
* Corresponding Author: M. Vilasini. Email: .
Computers, Materials & Continua 2020, 62(3), 1445-1472. https://doi.org/10.32604/cmc.2020.08857
Abstract
Leaf species identification leads to multitude of societal applications. There is
enormous research in the lines of plant identification using pattern recognition. With the
help of robust algorithms for leaf identification, rural medicine has the potential to
reappear as like the previous decades. This paper discusses CNN based approaches for
Indian leaf species identification from white background using smartphones. Variations
of CNN models over the features like traditional shape, texture, color and venation apart
from the other miniature features of uniformity of edge patterns, leaf tip, margin and
other statistical features are explored for efficient leaf classification.
Keywords
Cite This Article
M. Vilasini and P. Ramamoorthy, "Cnn approaches for classification of indian leaf species using smartphones,"
Computers, Materials & Continua, vol. 62, no.3, pp. 1445–1472, 2020.
Citations