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Leaf lesion classification (LLC) algorithm based on artificial bee colony (ABC)

Ahmad, Faudziah and Ku-Mahamud, Ku Ruhana and Sainin, Mohd Shamrie and Airuddin, Ahmad (2015) Leaf lesion classification (LLC) algorithm based on artificial bee colony (ABC). ARPN Journal of Engineering and Applied Sciences, 10 (3). pp. 1311-1315. ISSN 1819-6608

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In this paper, an algorithm to classify leaf disease severity based on lesions is presented. The algorithm involved three main steps, filtration, recognition and detection.Artificial Bee Colony, Fuzzy Logic, Otsu and Geometry formula were incorporated to achieve the goal.Ninety-four leaf images were used in this algorithm combination experiment.The study was conducted in four phases, filtration, recognition, detection and evaluation.Comparison was made with four other algorithms, Otsu, Canny, Robert and Sobel. Results showed that the Leaf Lesion Classification (LLC) algorithm based on Artificial Bee colony (ABC) produced an average 96.83% of accuracy and average 1.66 milliseconds of processing time, indicating that LLC algorithm is better than algorithm such as Otsu, Canny, Roberts and Sobel. The study makes a substantial contribution to the body of knowledge in image processing.

Item Type: Article
Uncontrolled Keywords: leaf lesion, fuzzy logic, area size, hybrid, artificial bee colony, otsu, geometry formula.
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: School of Computing
Depositing User: Dr. Faudziah Ahmad
Date Deposited: 14 Jul 2015 07:59
Last Modified: 27 Apr 2016 00:05
URI: http://repo.uum.edu.my/id/eprint/14839

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