Research Article
Classification of Leaf Diseases in Paddy Plant Based on Combined Approach of Texture and Colour Feature Extraction and Optimized Feature Selection
@INPROCEEDINGS{10.4108/eai.7-6-2021.2308780, author={Nithiya S and Annapurani K}, title={Classification of Leaf Diseases in Paddy Plant Based on Combined Approach of Texture and Colour Feature Extraction and Optimized Feature Selection}, proceedings={Proceedings of the First International Conference on Computing, Communication and Control System, I3CAC 2021, 7-8 June 2021, Bharath University, Chennai, India}, publisher={EAI}, proceedings_a={I3CAC}, year={2021}, month={6}, keywords={bahe k mean clustering pso firefly algorithms ga}, doi={10.4108/eai.7-6-2021.2308780} }- Nithiya S
Annapurani K
Year: 2021
Classification of Leaf Diseases in Paddy Plant Based on Combined Approach of Texture and Colour Feature Extraction and Optimized Feature Selection
I3CAC
EAI
DOI: 10.4108/eai.7-6-2021.2308780
Abstract
This paper proposes a methodology for the classification of leaf diseases by using the different characterization of shape, and colour properties. Paddy plant diseases are discussed in this research work. Bacterial light, Brown Spot, Leaf smut diseases is identified in paddy crops. A plant leaf is pre-processed at first utilizing the improved BAHE (brightness adapted histogram equalization). Leaf image is segmented using K mean clustering algorithm. The feature extraction is improved by combination of texture feature and colour features. The extracted feature is given as an input for feature selection using optimized firefly algorithm’s after that it is used for the classification of diseases in paddy plant. The optimization result is compared with PSO and Genetic algorithm..