Product Recognition Apparatus Using Weight Verification for Settlement Accuracy
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Solution Overview
Problem
Current settlement apparatuses struggle to recognize products with obscured or misaligned bar codes, leading to incomplete settlement processes and increased costs due to the need for weight measurement confirmation, which cannot detect unrecognized products effectively.
Innovation Solution
An article recognition apparatus with an image acquisition unit, recognition unit, region detection unit, and determination unit that acquires images, detects identification patterns, determines article regions, and identifies unrecognized products by comparing image regions with stored reference values, allowing for accurate product recognition and settlement without additional weight measurement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If weight measurement confirmation is used to verify product recognition, then settlement accuracy is improved, but device complexity and cost increase
Solution Approach 1:
The patent introduces an intermediary verification mechanism that compares the sum of recognized product weights with the total weight detected by the weighing sensor. This intermediary comparison step enables weight measurement confirmation without requiring direct integration of complex weighing systems into the recognition apparatus, thus improving settlement accuracy while controlling device complexity through modular design.
Solution Approach 2:
The weighing sensor serves multiple functions: it detects total weight for verification purposes, provides data for unrecognized product detection, and supports settlement accuracy validation. By making the weighing component multi-functional, the patent improves reliability without proportionally increasing device complexity, as the same hardware performs multiple verification tasks.
2Reliability
If weight measurement confirmation is used to detect unrecognized products, then recognition completeness is improved, but device complexity increases
Solution Approach 1:
The system implements a feedback mechanism where the weighing sensor continuously monitors total weight and compares it against the sum of recognized product weights. When a discrepancy is detected, the system generates feedback signals to identify unrecognized products and triggers re-scanning or alerts. This feedback loop improves recognition completeness by enabling continuous verification without requiring complex additional detection hardware.
Solution Approach 2:
The patent replaces complex mechanical detection systems with a simpler weight-based verification approach. Instead of using multiple cameras or sensors to detect each product's presence and orientation, the system uses a single weighing sensor to infer the presence of unrecognized products through weight discrepancy analysis, thereby improving recognition completeness while reducing device complexity.
3Measurement precision
If bar code recognition is used for product identification, then identification accuracy is improved, but adaptability decreases when bar codes are obscured or misaligned
Solution Approach 1:
The system performs preliminary weight measurement before product recognition to establish an expected total weight baseline. This preliminary action enables the system to anticipate and compensate for potential recognition failures due to obscured or misaligned bar codes, as the weight baseline provides a reference for detecting missing products even when visual identification fails, thereby improving adaptability without sacrificing identification accuracy for properly oriented products.
Solution Approach 2:
The weighing sensor acts as an intermediary verification layer between the bar code recognition system and the final settlement process. When bar code recognition fails or produces incomplete results, the weight measurement serves as an intermediate check to identify discrepancies and trigger corrective actions, thus enhancing adaptability to various product orientations and conditions while maintaining high identification accuracy for successfully scanned items.
Data Source
AI summary
According to one embodiment, an article recognition apparatus includes an image acquisition unit, a recognition unit, a region detection unit, a storage unit, and a determination unit. The recognition unit recognizes each of the articles. The region detection unit determines article region information. The storage unit stores article information including a reference value for the article region information. The determination unit determines that an unrecognized article exists, if the reference value for the article region information of each article which the recognition unit recognized does not match with the article region information.


