Carrot Disease Detection Using Image Processing

Abstract

Carrot is a famous nutritional vegetable and developed all through the world. Agriculture remains the most important sector of Bangladesh economy, contributing 19.6 percent to the national GDP and providing employment for 63 percent of the population. Agriculture in Bangladesh is heavily dependent on the weather, and the entire harvest can be wiped out in a matter of hours when cyclones hit the country. According to the World Bank, the total arable land in Bangladesh is 61.2 percent of the total land area (down from 68.3 percent in1980) Yet, Farmers actually developed this vegetable without using applicable logical inventions. This might prompt financial mischances just as lessen the benefit of drovers. As of now, vegetable illness causes loads of financial and natural issues. Be that as it may, beforehand discovery of vegetable illness can drop those mischances and can make drovers beam. Latterly, in our disquisition, we've proposed a Deep Literacy- grounded frame for carrot infection acknowledgment. We’ve explored different avenues regarding sound carrots and two normal carrot infections, for illustration, Depression spot of carrot, Leaf scar of carrot. We've employed Convolutional Neural Network (CNN) to include birth neural purposes and Fully Convolutional Neural Network model (FCNN) for infection order. Convolutional Network is an extraordinary outfit for picture highlight birth, and it lessens the difficulty of homemade element birth. We've explored different avenues regarding different convolutional models with colorful layers and our proposed Convolutional model gives us a perfection of virtually 99%, which is surely useful for the drovers to distinguish carrot illness and boost their advantage.