International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 10 Issue: 05 | May 2023
p-ISSN: 2395-0072
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Plant Disease Detection System Shraddha Trivedi1, Jay Shukla2 ---------------------------------------------------------------------***--------------------------------------------------------------------With the help of the Plant Disease Detection System, Abstract - The Plant Disease Detection System is a cutting-
growers and gardeners can quickly, accurately, and affordably keep track on the health of their plants. A variety of plant diseases can produce subtle changes in the look of leaves, stems, and fruits, which this technique can identify. Farmers and gardeners can take proactive steps to stop the spread of disease and safeguard their crops by spotting infections early on. In the long run, this can boost agricultural output and support food security around the world.
edge tool that precisely identifies and categorises plant diseases using machine learning and computer vision techniques. By immediately detecting and diagnosing diseases before they spread and do substantial harm, this technology can help farmers and gardeners keep an eye on the health of their plants and harvests. The system can recognise tiny changes in the look of leaves, stems, and fruits brought on by various plant diseases by using image recognition techniques and deep learning algorithms like VGG19 and CNN. The Plant Disease Detection System is a priceless tool for guaranteeing healthy plant growth and raising agricultural productivity because of its precision and effectiveness.
The way we keep an eye on plant health and deal with diseases could be completely changed by the Plant Disease Detection System. From modest gardens to enormous industrial farms, it can be applied in a variety of environments. The adoption of this technology will help promote environmentally responsible farming practises.
Key Words: Image recognition, Machine Learning, Deep learning models, Visual Inspection, Convolutional Neural Network (CNN), VGG19 Algorithm, Early Detection, Environmental stewardship, Automated System.
2. LITERATURE REVIEW "Plant leaf disease detection using Computer Vision and Machine Learning Algorithms" by Sunil S.Harakannanavar, Jayashri M. Rudagi , Veena Puranikmath, Ayesha Siddiqua, R Pramodhini [1]
1. INTRODUCTION Plants are a vital component of human life since they offer food, medicine, and a variety of other advantages. They are essential to the ecosystem and help ensure the sustainability of the entire planet. Yet, a vast range of ailments involving fungi, bacteria, viruses, and environmental pressures can affect plants. Plant diseases have the potential to drastically lower output, quality, and even cause crop collapse. For the safety of the food supply, the health of the economy, and the sustainability of the environment, this might have disastrous effects.
In this research firstly, Pre-processing by image resizing, contrast takes place. Then Enhancement and color-space conversion followed by segmentation of image is applied for background subtraction. The classification approach is carried out by KNN, ANN and SVM method. Its fundamental motive is easing the process of distinction of plants for disease detection. "A Study on Various Techniques for Plant Leaf Disease Detection Using Leaf Image” by Sakshi Raina and Abhishek Gupta [2]
The traditional approach to identifying and diagnosing plant diseases relies on visually inspecting the affected plants, which can be time-consuming, expensive, and occasionally erroneous. The proficiency and experience of the individual doing the inspection will determine how accurate these approaches are. To stop their spread and lessen their effects, automated methods that can swiftly and precisely identify plant diseases are required.
The authors of this article give a quick summary of the many classifications of plant diseases utilising artificial neural networks, deep learning, and machine learning. Image acquisition, image preprocessing, picture segmentation, analysis, and classification are the fundamental phases in illness detection. Combining computer vision with plant disease detection methods is the primary goal of this paper.
In order to identify and treat plant illnesses in real-time, the Plant Disease Detection System uses computer vision and machine learning techniques. Several methods, including drones, smartphones, and other imaging equipment, are used in this system to capture photographs of the plants. After that, these photos are analysed to find illness indicators utilising sophisticated image processing methods and deep learning models.
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