International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 11 Issue: 06 | Jun 2024
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p-ISSN: 2395-0072
Report on Leaf Disease Detection Using Image Processing Ghanashyam M*1, Sumanth B N *2 , Prof.Vidya Shankar *3, Puneetha M P*4 *1UG Scholar (BCA),Dept. of computer science, JSS College Arts, Commerce, Science (JSSCACS), Mysore, Karnataka,
India
*2UG Scholar (BCA),Dept. of computer science, JSS College Arts, Commerce, Science (JSSCACS), Mysore, Karnataka,
India
*3 HOD and Professor, Dept. of computer science, JSS College Arts, Commerce, Science (JSSCACS), Mysore,
Karnataka, India
*4 Asst. Professor, Dept. of computer science, JSS College Arts, Commerce, Science(JSSCACS), Mysore, Karnataka,
India ---------------------------------------------------------------------------***---------------------------------------------------------------------Abstract – uses image processing techniques because images are a valuable source of information and data for biological Farmers need automatic disease monitoring systems in science. Digital image processing and image analysis order to improve crop development and yield. It takes a technology, which are based on advancements in micro lot of time and experience, which is often expensive or electronics and computers, have numerous biological unavailable, to perform manual monitoring, which is out applications. of date. With an emphasis on leaves and fruits, this paper presents a novel method for quickly and accurately 1.2Theproject'shistory detecting plant diseases through the use of digital image Disease identification heavily relies on image processing. For disease detection and classification, the segmentation, which is the process of breaking a suggested approach combines a multi-SVM algorithm picture up into its component pieces. There are several with a k-means clustering technique in MATLAB. About approaches available, ranging from basic thresholding 70% of the people in India is dependent on agriculture, to sophisticated colour image segmentation. In order to which is the backbone of the country's economy. Crop find distinct features that would be difficult for diseases are frequently the result of changes in the computers to recognize without intelligent processing, climate, such as intense rainfall and temperature swings. this study uses evolutionary algorithms for colour It takes a lot of time and money to diagnose severe image segmentation. illnesses using conventional methods, thus professional assistance is required. In order to detect plant diseases 1.3 The Project's Goal effectively and accurately, this research explores a contemporary method that uses image processing The objective is to increase the accuracy of leaf techniques. It focuses specifically on leaf infections. disease detection. Key Words: capturing images, preliminary processing, Partitioning the leaf according to disease status feature extraction categorizing, neural net. The goal is to obtain the input of the processed leaf image. 1.INTRODUCTION The K-Means clustering algorithm will be used to segment the image. India is a country based mostly on agriculture. Lastly, use an SVM classifier to determine the Agriculture accounts for 70% of India's GDP. Crops disease type and severity level that has affected become infected as a result of climatic changes such as the leaf. intense rainfall and sharp temperature swings. And combines and synthesizes prior understanding those can be identified by defoliation, colour changes, of a topic. spots on the leaf, and dryness of the leaf. The majority Illustrates how you have applied other people's of people are unable to quickly and correctly recognise knowledge and how your research has the illness. We need specialists who can diagnose the generated new concepts. illness in order to accomplish it. However, this is a more costly and time-consuming procedure. The suggested project, which aims to detect leaf infections, © 2024, IRJET
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