Detection and Grading of Multiple Fruits and Vegetables Using Machine Vision
Renju Rachel Varghese, Pramod Mathew Jacob, S. Sooraj, Daniel Mathew Ranjan, Jino Cherian Varughese, Hegsymol Raju
Abstract
Quality of fruits and vegetables has much relevance in the modern health consortium. Grading of fruits based on the quality is the prime solution. But traditional fruit grading mechanisms are not feasible due to the mass production of fruits and vegetables. Technological advancements in the field of agriculture can help to increase productivity and thereby reduce the selling of damaged or defective products. We propose a real-time fruit and vegetable grading system using Machine Vision to help all users to choose the ideal fruit or vegetable for consumption. Our proposed model will also predict the shelf life of the identified fruit. An Android application is used to scan the fruit or vegetable image in real-time. The features of the objects are extracted, and the data is processed. The chemical ripening in the fruit/vegetable is also detected. Our experimental results show that this mobile application will be useful to the common people for estimating the fruit /vegetable quality along with its shelf life.