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Measuring the Severity of Fungi Caused Disease on Leaves using Triangular Thresholding Method

Dominic Asamoah, Richard Marfo, Stephen Opoku Oppong. Published in Image Pprocessing

International Journal of Applied Information Systems
Year of Publication: 2017
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors: Dominic Asamoah, Richard Marfo, Stephen Opoku Oppong
10.5120/ijais2017451668
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  1. Dominic Asamoah, Richard Marfo and Stephen Opoku Oppong. Measuring the Severity of Fungi Caused Disease on Leaves using Triangular Thresholding Method. International Journal of Applied Information Systems 12(1):24-32, April 2017. URL, DOI BibTeX

    @article{10.5120/ijais2017451668,
    	author = "Dominic Asamoah and Richard Marfo and Stephen Opoku Oppong",
    	title = "Measuring the Severity of Fungi Caused Disease on Leaves using Triangular Thresholding Method",
    	journal = "International Journal of Applied Information Systems",
    	issue_date = "April 2017",
    	volume = 12,
    	number = 1,
    	month = "Apr",
    	year = 2017,
    	issn = "2249-0868",
    	pages = "24-32",
    	url = "http://www.ijais.org/archives/volume12/number1/980-2017451668",
    	doi = "10.5120/ijais2017451668",
    	publisher = "Foundation of Computer Science (FCS), NY, USA",
    	address = "New York, USA"
    }
    

Abstract

Leaf disease detection and measurement is one of the most difficult tasks in agricultural image processing. This study discus in details the methods and means of detecting and measuring the severity of fungi caused disease on plant leaves using the triangular thresholding method. Four suspected images ware collected from different plant species and experiments were conducted on each to detect and measure the extent of damage caused by the fungi cause disease on the leaf. Analysis was made and the results proved to be about 97% accurate.

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Keywords

Segmentation, Thresholding, Image Acquisition, Triangular Thresholding, Leaf Disease