Research Article
Diagnosis of Plant Diseases by Image Processing Model for Sustainable Solutions
@INPROCEEDINGS{10.1007/978-3-031-35081-8_15, author={Sasmita Pani and Jyotiranjan Rout and Zeenat Afroz and Madhusmita Dey and Mahesh Kumar Sahoo and Amar Kumar Das}, title={Diagnosis of Plant Diseases by Image Processing Model for Sustainable Solutions}, proceedings={Intelligent Systems and Machine Learning. First EAI International Conference, ICISML 2022, Hyderabad, India, December 16-17, 2022, Proceedings, Part II}, proceedings_a={ICISML PART 2}, year={2023}, month={7}, keywords={diseases image processing trained data}, doi={10.1007/978-3-031-35081-8_15} }- Sasmita Pani
Jyotiranjan Rout
Zeenat Afroz
Madhusmita Dey
Mahesh Kumar Sahoo
Amar Kumar Das
Year: 2023
Diagnosis of Plant Diseases by Image Processing Model for Sustainable Solutions
ICISML PART 2
Springer
DOI: 10.1007/978-3-031-35081-8_15
Abstract
The first step in preventing losses in agricultural product output and quantity is to identify plant diseases. A significant loss in crop output and market economic value results due to incorrect identification. The farmers used their own eyesight or prior knowledge of plant illnesses to identify plant ailments. When farmers are doing this for a single plant, it is possible, but when it involves many distinct plants, it is much more challenging to detect and takes a lot of effort. Therefore, it is preferable to utilize image processing to detect plants diseases. Image acquisition, picture pre-processing, image segmentation, feature extraction, and classification are all processes in this approach to diagnose the plant disease. In this study, we would like to present the procedures for identifying plant diseases from their leaf photos. We have used VGG 19 model for efficient processing of trained data and test data. This paper aims to support and help the green house farmers in an efficient way.
