House Plant Leaf Disease Detection and Classification Using Machine Learning

Abstract

Hibiscus is a fantastic herb, and in Ayurveda, it is one of the most renowned herbs that have extraordinary healing properties. Hibiscus is rich in vitamin C, flavonoids, amino acids, mucilage fiber, moisture content, and antioxidants. Hibiscus can help with weight loss, cancer treatment, bacterial infections, fever, high blood pressure, lower body temperature, treat heart and nerve diseases. Automatic leaf disease detection is an essential task. Image processing is one of the popular techniques for the plant leaf disease detection and categorization. In this chapter, the diseased leaf is identified by concurrent k-means clustering algorithm and then features are extracted. Finally, reweighted KNN linear classification algorithms have been used to detect the diseased leaves categories.

Evaluation of Machine Learning Models for Plant Disease Classification Using Modified GLCM and Wavelet Based Statistical Features

“…Barbedo [5] has experimented on the effect of the size of the dataset and image background for effectively analysing the plant disease clategorization. Usharani [6] has worked on the house plant leaf (Hibiscus herb) disease detection and classification using K-nearest neighbor (KNN) algorithm. Sabrol and Satish [7] have used a classification tree for the purpose of tomato plant disease classification based on five types of tomato disease.…”