Analysis of Diseases in Farm Crops Using Image Processing and Machine Learning Techniques

DOI

10.2991/978-94-6463-471-6_35How to use a DOI?

Keywords

Image processing; Image Acquisition; Pre-processing; Feature Extraction; Neural networks; Activation Function and Pooling Layers

Abstract

The existence of plant diseases is a matter of considerable health apprehension for all forms of life. Timely identification of diseases enables farmers to promptly implement the required remedies, thereby enhancing agricultural productivity. Machine learning stands at the forefront of modern technology, serving as the foundation for precision agriculture by facilitating the creation of sophisticated techniques for disease detection and classification. This project delves into the detection of plant diseases through the use of visual recognition technology. Upon uploading an image of the infected leaf to our application, it will undergo analysis. The application will then promptly identify the disease and provide recommended preventive methods directly within the application. Managing diseases poses a formidable challenge. Diseases are predominantly observed on the leaves or stems of plants. Accurately measuring diseases, pests, and traits that are visually observed has not been thoroughly explored due to the intricate nature of visual patterns. This paper introduces an approach for identifying leaf diseases through the utilization of advanced machine learning and image processing methods, addressing the escalating demand for enhanced and accurate image pattern recognition in this context. Using image processing and CNNs for detecting plant diseases involves capturing and preprocessing plant images, extracting relevant features, and then using a CNN to learn and identify patterns indicative of diseases. Image Processing involves Image Acquisition, Pre-processing and Feature Extraction, whereas CNN involves Convolutional Layers, Activation Function, Pooling Layers, Fully Connected Layers and Output Layers.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - C. Siva Kumar
AU  - Kodadala Charishma Reddy
AU  - Mounika Annam
AU  - Ch Govardhan Reddy
AU  - Enamala Pujith
PY  - 2024
DA  - 2024/07/30
TI  - Analysis of Diseases in Farm Crops Using Image Processing and Machine Learning Techniques
BT  - Proceedings of the International Conference on Computational Innovations and Emerging Trends (ICCIET- 2024)
PB  - Atlantis Press
SP  - 354
EP  - 360
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-471-6_35
DO  - 10.2991/978-94-6463-471-6_35
ID  - Kumar2024
ER  -