Smart Computing- Book ISBN- 978-81-953658-1-4

Authors:- Amit Singh, Mayank Shukla, Abhishek Yadav, Nirali Bhaliya

Abstract :-Plant Identification of the plant ailments is the key to stopping the losses in the yield and extent of the agricultural product. The research of the plant ailments implies the research of visually observable patterns viewed on the plant. Health monitoring and ailment detection on the plant is very imperative for sustainable agriculture. It is very hard to screen the plant illnesses manually. It requires a first-rate quantity of work, expertise in plant diseases and additionally requires immoderate processing time. Hence, image processing is used for the detection of plant diseases. Plant Disease Identification includes photo acquisition, picture pre-processing, picture segmentation, characteristic extraction and classification. In our proposed work, AlexNet, which is used as a feature extractor, plays a very crucial role in helping to classify plant diseases. We have proposed an image-processing based technique to identify plant diseases. This method takes an image of the affected plant disease as input. It will extract the key features using filters, and extracted features are then compared with the trained model (contains datasets of sample images) to detect the type of plant disease. Our Proposed work is simple, quick, and does not require any costly equipment.

Keywords: - Image Processing, AlexNet, Skin diseases, Feature Extraction