Proceedings ArticleDOI
Leaf disease detection on cucumber leaves using multiclass Support Vector Machine
P. Krithika,S. Veni +1 more
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TLDR
K-means clustering, an unsupervised algorithm along with Support Vector Machine(SVM) is used in this work to address the issue of diseases present in the leaf of salad cucumber using computer aided image processing technique.Abstract:
In India, smart organic farming is gaining importance. There may be problems due to environment, temperature, humidity or nutrient deficiency in this farming. If we have a monitoring system for this farming it is possible to produce healthy plant. The aim is to address this issue using computer aided image processing technique. Main solution is to create an automation system which can detect the disease present in the leaf of the plant. In this paper, a first level attempt is made to detect diseases present in the leaf of salad cucumber. The most common diseases which are present in salad cucumber are Alternaria leaf blight, Bacterial wilt, Cucumber green mottle mosaic, Leaf Miner, Leaf spot, Cucumber Mosaic Virus (CMV) disease and so on. K-means clustering, an unsupervised algorithm along with Support Vector Machine(SVM) is used in this work to address this problem.read more
Citations
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A Color and Texture Based Approach for the Detection and Classification of Plant Leaf Disease Using KNN Classifier
TL;DR: In this work, KNN classifier will classify the diseases like alternaria alternata, anthracnose, bacterial blight, leaf spot, and canker of various plant species using textures extracted from the leaf disease images for the classification.
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Affordable Smart Farming Using IoT and Machine Learning
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TL;DR: An affordable system which when deployed will give an insight into the real time condition of the crop and uses state-of-the-art methods in order to improve the accuracy of the results and automate the monitoring of crops thereby requiring minimal human intervention.
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Plant Leaf Disease Detection using Computer Vision and Machine Learning Algorithms
TL;DR: 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).
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Smart Agriculture Based on IoT and Machine Learning
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References
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Image processing
TL;DR: Parts of image processing are discussed--specifically: the mathematical operations one is likely to encounter, and ways of implementing them by optics and on digital computers; image description; and image quality evaluation.
Proceedings Article
Image Processing
TL;DR: The main focus in MUCKE is on cleaning large scale Web image corpora and on proposing image representations which are closer to the human interpretation of images.
Proceedings ArticleDOI
A framework for detection and classification of plant leaf and stem diseases
TL;DR: The experimental results indicate that the proposed approach can significantly support accurate and automatic detection of leaf diseases and the developed Neural Network classifier that is based on statistical classification perform well and could successfully detect and classify the tested diseases with a precision of around 93%.
Proceedings ArticleDOI
Rice disease identification using pattern recognition techniques
Santanu Phadikar,Jaya Sil +1 more
TL;DR: A software prototype system for rice disease detection based on the infected images of various rice plants is described, which is both image processing and soft computing technique applied on number of diseased rice plants.