Title: Comparison of automated leaf recognition techniques

Authors: Sk Mahmudul Hassan; Arnab Kumar Maji

Addresses: Department of Information Technology, North Eastern Hill University, Shillong, India ' Department of Information Technology, North Eastern Hill University, Shillong, India

Abstract: Plant plays an important role in different ways in human life and atmosphere. There are large numbers of plant species in the world. Plant species plays a vital role in many domains such as preventing some of the diseases, farming, environment, discovery of new drug and other related areas. Recognition of plant species without expert understanding is a huge task. There has been great demand for applying automatic computer vision technologies to increase botanical knowledge. Using leaf features and traits, the classification and identification of plant is carried out. Leaf features like shape, texture and venation are the features most frequently used to differentiate the plant species. Different methodologies are there to extract the feature and to classify the leaf images using a classifier. In this paper we are going to discuss on different leaf recognition approaches along with feature extraction methods and their performances.

Keywords: artificial neural network; ANN; convolution neural network; CNN deep learning; probabilistic neural network; PNN; support vector machine; SVM.

DOI: 10.1504/IJIE.2021.114503

International Journal of Intelligent Enterprise, 2021 Vol.8 No.2/3, pp.205 - 214

Received: 29 Jun 2018
Accepted: 14 Jan 2019

Published online: 05 Mar 2021 *

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