Image-Based Payment Recognition for Self-Checkout Loss Prevention

The patent introduces an image analysis system as an intermediary between the customer and the payment system. The system captures images of the checkout area, analyzes them using AI algorithms to detect whether commodities are properly scanned, and triggers alerts when suspicious behavior is detected. This intermediary automated monitoring mechanism maintains customer convenience while preventing property loss through intelligent detection rather than human supervision.

The patent replaces the mechanical system of human supervision with an automated image analysis system. The system uses cameras to capture images, AI algorithms to analyze them, and automated alert mechanisms to notify staff only when suspicious behavior is detected. This substitution eliminates the need for continuous human monitoring while maintaining effective loss prevention, thereby significantly reducing manpower consumption.

The patent implements a self-service automated detection system that independently performs image capture, analysis, and alert generation without requiring human intervention. The AI-based image analysis system automatically processes checkout area images, identifies suspicious behaviors such as intentional missing scans, and triggers notifications. This self-service mechanism enhances both detection capability and operational efficiency by eliminating manual review processes.

The patent applies preliminary action by capturing multiple images continuously during the checkout process rather than analyzing a single image after the fact. The system takes images at different time points showing the progression of the customer's actions, allowing the AI to track behavior patterns in real-time. This approach maintains high recognition accuracy while reducing processing time by performing analysis incrementally as images are captured, rather than waiting to collect all images before analysis.