Abstract: The study of plants is known as botany and for any botanist it is a daily routine work to examine various plants in their research lab. This research efforts an image processing-based algorithm for extracting the region of interest (ROI) from plant leaf in order to classify the specie and to recognize the particular botanical disease as well. Moreover, this paper addresses the implementation of curvelet transform on subdivided leaf images in order to compute the related information and train the support vector machine (SVM) classifier to execute better results. Furthermore, the paper presents a comparative analysis of existing and proposed algorithm for species and botanical diseases recognition over the dataset of leaves. The proposed multi-dimensional curvelet transform based algorithm provides relatively greater accuracy of 93.5% with leaves dataset.

Nazish Tunio, Abdul Latif Memon, Faheem Yar Khuhawar and Ghulam Mustafa Abro, “Detection of Infected Leaves and Botanical Diseases using Curvelet Transform” International Journal of Advanced Computer Science and Applications(IJACSA), 10(1), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0100166

@article{Tunio2019,
title = {Detection of Infected Leaves and Botanical Diseases using Curvelet Transform},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0100166},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0100166},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {1},
author = {Nazish Tunio and Abdul Latif Memon and Faheem Yar Khuhawar and Ghulam Mustafa Abro}
}