Information processing apparatus, information processing method, and program for identifying whether an advertisement is positioned in association with a product

The patent replaces the manual mechanical checking process with an automated image recognition system. The system captures images of shelf racks, uses computer vision algorithms to automatically detect advertisement positions and product locations, and compares them against predefined placement rules. This substitution eliminates manual labor while maintaining verification accuracy through automated image analysis and position calculation.

The system enables self-service verification by automatically performing the entire advertisement placement checking process without human intervention. The image recognition system independently captures images, processes them to identify advertisements and products, calculates positions, applies verification rules, and generates reports. This self-service capability dramatically improves productivity while reducing time loss.

The patent implements a multi-functional integrated system that performs multiple tasks within a single automated framework. The image recognition system simultaneously captures images, detects advertisements, identifies products, calculates positions, applies verification rules, and generates reports. This universal approach consolidates what could be multiple separate complex systems into one unified automation platform, managing complexity through functional integration.

The system introduces an intermediary image processing layer between the physical advertisement placement and the verification decision. This intermediary layer captures visual information, converts it into digital data through image recognition, and processes it according to predefined rules. This intermediary approach simplifies the overall system by creating a standardized data transformation pipeline that mediates between physical reality and automated decision-making.

The system performs preliminary actions by pre-defining verification rules, advertisement regions of interest, and expected product locations before image analysis begins. The image recognition process is guided by these pre-established parameters, which narrow the search space and allow the system to focus computational resources on critical detection areas. This preliminary preparation enables faster processing while maintaining high position detection accuracy.

The patent applies local quality optimization by focusing image analysis resources on specific critical regions rather than processing the entire image uniformly. The system identifies and prioritizes analysis of advertisement areas, product locations, and boundary regions where placement accuracy is most critical. By concentrating computational effort on these local regions of interest, the system achieves high measurement precision without the computational overhead of exhaustive full-image analysis.