Open Access

ARTICLE

CNN Approaches for Classification of Indian Leaf Species Using Smartphones

M. Vilasini^{1, *}, 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.

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