학술논문

Leaf Recognition and Disease Detection using Content based Image Retrieval
Document Type
Conference
Source
2021 7th International Conference on Advanced Computing and Communication Systems (ICACCS) Advanced Computing and Communication Systems (ICACCS), 2021 7th International Conference on. 1:243-247 Mar, 2021
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
General Topics for Engineers
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Productivity
Image recognition
Communication systems
Image retrieval
Support vector machine classification
Diseases
Image Processing
K-means clustering
Support Vector Machine
K-Nearest Neighbours
Language
ISSN
2575-7288
Abstract
The agricultural domain in past few decades has seen a decrease in its productivity. The main cause for this was found to be an increase in plant diseases. Having diseases in plants is quite common, but due to improper care there have been serious effects on plants. But we cannot keep inspecting each and every plant present in thousands. Hence, in this work an approach is developed which provides faster and more accurate results of the detected plant leaves and its corresponding diseases. The proposed work approach uses various image processing techniques for recognising the plant leaf type and detecting disease. The system uses two different classification methods namely, Support Vector Machine (SVM) and K-Nearest Neighbours (KNN) and their performances are compared.