Detection of plant leaf diseases using image segmentation and soft computing techniques

By V. Singh, A. K. Misra. 2017

1,146 citations recorded by the source corpus.

Abstract Agricultural productivity is something on which economy highly depends. This is the one of the reasons that disease detection in plants plays an important role in agriculture field, as having disease in plants are quite natural. If proper care is not taken in this area then it causes serious effects on plants and due to which respective product quality, quantity or productivity is affected. For instance a disease named little leaf disease is a hazardous disease found in pine trees in United States. Detection of plant disease through some automatic technique is beneficial as it reduces a large work of monitoring in big farms of crops, and at very early stage itself it detects the symptoms of diseases i.e. when they appear on plant leaves. This paper presents an algorithm for image segmentation technique which is used for automatic detection and classification of plant leaf diseases. It also covers survey on different diseases classification techniques that can be used for plant leaf disease detection. Image segmentation, which is an important aspect for disease detection in plant leaf disease, is done by using genetic algorithm.

Subfields: Analytical Chemistry, Plant Science

View Paper: https://www.semanticscholar.org/paper/d6ae998fc1d27bc8e9ad282f6806cad92e299e80

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In Analytical Chemistry

In Plant Science

Citations in the corpus

An advanced deep learning models-based plant disease detection: A review of recent research (2023, methodology): “These methods involve training a network to learn the underlying features of the images, enabling the identification of subtle symptoms of diseases that traditional image processing methods may not be able to detect (Singh and Misra, 2017; Khan et al., 2021; Liu and Wang, 2021b).”
Identification and recognition of rice diseases and pests using convolutional neural networks (2018, background): “ted Works Many approaches have been applied to correctly identify plant diseases from images. Most of them use general image processing techniques, SVM classier, K-mean clustering, genetic algorithm [11] etc. Hand engineered features often re ect our limited knowledge about an image, and so, we cann”
An optimized dense convolutional neural network model for disease recognition and classification in corn leaf (2020, background): “Detection of leaf diseases through visual observation requires a team of specialists and constant crop monitoring [4].”
Plant disease detection and classification techniques: a comparative study of the performances (2024, background): “The authors of [46] have presented an image segmentation algorithm for the automatic detection and classification of plant leaf diseases.”
Early Detection and Classification of Tomato Leaf Disease Using High-Performance Deep Neural Network (2021, background): “These objects are used to determine regions of interest as infected regions in the image [18].”