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Title: Leaf lesion classification (LLC) algorithm based on artificial bee colony (ABC)
Authors: Faudziah Ahmad, Ku Ruhana Ku-Mahamud, Mohd Shamrie Sainin, Ahmad Airuddin
Journal: ARPN Journal of Engineering and Applied Sciences
Publisher: Khyber Medical College, Peshawar
Country: Pakistan
Year: 2015
Volume: 10
Issue: 3
Language: English
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.
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