IMAGE PROCESSING AND DEEP LEARNING FOR SMART TROLLEY SYSTEM

A shopping trolleyis a cart for the use ofcustomers inside the shop for transport their itemsto the checkout counter during shopping. There is a major disadvantage for the customers to stand in long billing queues in shopping malls. The objective of the project is to make a Smart Shopping trolley system that uses image processing and deep learning concept for real time object recognition without human interference. It makes use of YOLO algorithm in deep learning to process the images of the objects picked by the customer with the help of a webcam. Here, the machine is trained to detect and identify a list of objects and this list can be expanded further based on the requirement using OpenCv. So, when an object’s image is captured in the webcam, it detects the object and identifies its name based on the training it has undergone. This result of image processing can be taken for further use in cloud storage, processing andtransferred to various devices and applications using cloud. Our objective was to give society an efficient and precise way of image processing which can be used in applications aiming to perform object detection.