Intra Class Vegetable Recognition System using Deep Learning
P Sudharshan Duth, K. Jayasimha
Abstract
Computer vision and pattern recognition is an emerging area in recognizing objects in an image. The technologies for recognizing objects in images have a wide range of applications such as vegetable and fruit detection systems, vehicle detection, and other systems. Our research work focuses on the detection of vegetable varieties into developing an efficient vegetable recognition system. The vegetables may appear the same by color and other features, for example, red tomato and red capsicum as the same color so using features for detecting vegetables may lead to false detection so this research work proposes an intraclass vegetable recognition system using deep learning. Deep learning used to detect the vegetable category by extracting and learning the images and explored the convolution neural network (CNN). From the results of the evaluation, intraclass vegetables recognized accurately with 95.50% and efficiently using deep learning.