Minimizing Checkout Time: A Vision-Based Solution for Produce Identification

This project focuses on the development of a self-checkout system for produce. The system integrates a camera and a digital scale to automate the process of identifying and pricing fruits and vegetables. The camera captures images of the produce to determine its type using image recognition techniques, while the scale measures its weight. By combining these two sources of data, the system automatically calculates the price of the selected product, streamlines the checkout process, reduces human error, and improves efficiency in retail environments. The proposed system measures and recognizes produce in 4 seconds in average.