Image-Based Plant Disease Detection - Palanisamy, Jayapriya
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This book explores an advanced approach to automatic marker-based morphological image segmentation, classification, and disease detection in diseased tomato plants using Support Vector Machine (SVM) classification. It delves into how morphological processing enhances image segmentation accuracy, enabling precise identification of diseased regions in tomato plants. The book also discusses feature extraction techniques, classification methods, and the effectiveness of SVM in distinguishing between healthy and diseased plant areas. This work is particularly useful for researchers, agronomists,…mehr

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Produktbeschreibung
This book explores an advanced approach to automatic marker-based morphological image segmentation, classification, and disease detection in diseased tomato plants using Support Vector Machine (SVM) classification. It delves into how morphological processing enhances image segmentation accuracy, enabling precise identification of diseased regions in tomato plants. The book also discusses feature extraction techniques, classification methods, and the effectiveness of SVM in distinguishing between healthy and diseased plant areas. This work is particularly useful for researchers, agronomists, and computer vision experts working on precision agriculture and plant disease diagnosis using deep learning and machine learning techniques.
Autorenporträt
Assistant Professor in UG Department of Computer Science, NGM College,Pollachi. Completed  PhD in NGM College. More than 13 Years of teaching experience with specialization in Digital Image processing, Operating System, Deep learning and Machine Learning. Published more than 15 research articles in reputed journals like IEEE,UGC care and Scopus.