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Texture-Based Feature Extraction Using Gabor Filters to Detect Diseases of Tomato Leaves

刊名：	Revue d'Intelligence Artificielle
作者：	Wiharto（Department of Informatics, Universitas Sebelas Maret） Fikri Hashfi Nashrullah（Department of Informatics, Universitas Sebelas Maret） Esti Suryani（Department of Informatics, Universitas Sebelas Maret） Umi Salamah（Department of Informatics, Universitas Sebelas Maret） Nurcahya Pradana Taufik Prakisya（Department of Educational Informatics, Universitas Sebelas Maret） Sigit Setyawan（Department of Medicine, Universitas Sebelas Maret）
刊号：	737F0004
ISSN：	0992-499X
出版年：	2021
年卷期：	2021, vol.35, no.4
页码：	331-339
总页数：	9
分类号：	TP3
关键词：	Gabor filter；Machine learning；Support vector machine；Texture；Color；Tomato disease
参考中译：
语种：	eng
文摘：	The disease in tomato plants, especially on tomato leaves will have an impact on the quality and quantity of tomatoes produced. Handling disease on tomato leaves that must be done is to detect the type of disease as early as possible, then determine the treatment that must be done. Detection of its types of tomato plant diseases requires sufficient knowledge and experience. The problem is that many beginner farmers in growing tomatoes do not have much knowledge, so they have failed in growing tomatoes. Based on these cases, this study proposes a model for the early detection of disease in tomato leaves based on image processing. The research method used is divided into 5 stages, namely preprocessing, segmentation, feature extraction, classification, and performance evaluation. The feature extraction stage used is texture-based with Gabor filters and color-based filters. The final decision is determined by the Support Vector Machine (SVM) classification algorithm with the Radial Basis Function (RBF) kernel. The test results of the tomato leaf disease detection system produced an average performance parameter of 98.83% specificity, 90.37% sensitivity, 90.34% F1-score, 90.37% accuracy, and 94.60% area under the curve (AUC). Referring to the resulting of the AUC performance, the tomato leaf disease detection system is in the very good category.