Real-time Scene Change Detection with Object Detection for Automated Stock Verification

Automation is a process of utilizing technology to reduce human efforts. In this paper, we propose a computer vision-based automated system for stock management in the supermarkets. The proposed system will help to reduce the manpower required in a supermarket by continuously monitoring the availability product in the supermarket and reporting the useful information to the concerned person automatically. The key idea behind the proposed scheme is that a few low-cost cameras will be placed in the supermarket which will help to capture the videos of the product racks in the supermarket. The presence of human beings are identified by using a structural similarity index (SSIM) based scene change detection technique, further, an object detection technique will be used to count the number of items present in the specific p roduct r ack. If t he number of items present in a particular rack goes below a threshold limit, a short message service (SMS) and/or email will go the concerned authority. To make it more comfortable, a product identifier ( printed) w ill b e k ept j ust b elow t he p roduct racks. An optical character recognition module in the proposed scheme will identify the product identifier a nd i t w ill b e m entioned in the SMS or email which will help the supervisor for scheduling the replacement of the items in the racks. The experimental study is carried out by placing sample items on a rack and the mobile camera is used as an IP camera with the help IP webcam android application for the monitoring purpose. The experimental study shows that the proposed scheme will work reliably in a supermarket environment.