Plant Leaf Disease Detection using Computer Vision and Machine Learning Algorithms
TLDR
In this article , the authors proposed a method to detect the leaf diseases in the tomato plant using support vector machine (SVM), convolutional neural network (CNN), and K-Nearest Neighbor (K-NN).Abstract:
Agriculture provides food to all the human beings even in case of rapid increase in the population. It is recommended to predict the plant diseases at their early stage in the field of agriculture is essential to cater the food to the overall population. But it unfortunate to predict the diseases at the early stage of the crops. The idea behind the paper is to bring awareness amongst the farmers about the cutting-edge technologies to reduces diseases in plant leaf. Since tomato is merely available vegetable, the approaches of machine learning and image processing with an accurate algorithm is identified to detect the leaf diseases in the tomato plant. In this investigation, the samples of tomato leaves having disorders are considered. With these disorder samples of tomato leaves, the farmers will easily find the diseases based on the early symptoms. Firstly, the samples of tomato leaves are resized to 256 × 256 pixels and then Histogram Equalization is used to improve the quality of tomato samples. The K-means clustering is introduced for partitioning of dataspace into Voronoi cells. The boundary of leaf samples is extracted using contour tracing. The multiple descriptors viz., Discrete Wavelet Transform, Principal Component Analysis and Grey Level Co-occurrence Matrix are used to extract the informative features of the leaf samples. Finally, the extracted features are classified using machine learning approaches such as Support Vector Machine (SVM), Convolutional Neural Network (CNN) and K-Nearest Neighbor (K-NN). The accuracy of the proposed model is tested using SVM (88%), K-NN (97%) and CNN (99.6%) on tomato disordered samples. read more
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References
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Detection of plant leaf diseases using image segmentation and soft computing techniques
Vijai Singh,Anoop Misra +1 more
TL;DR: An algorithm for image segmentation technique which is used for automatic detection and classification of plant leaf diseases and also covers survey on different diseases classification techniques that can be used for plant leaf disease detection.
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Detection of leaf diseases and classification using digital image processing
TL;DR: Texture features are extracted using statistical Gray-Level Co-Occurrence Matrix (GLCM) features and classification is done using Support Vector Machine (SVM) using statistical GLCM features.
Journal ArticleDOI
Demand side management of small scale loads in a smart grid using glow-worm swarm optimization technique
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