Product Quantity Detection via Multi-Image Exclusion Logic
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Solution Overview
Problem
Existing product quantity determination systems face challenges in accurately detecting the quantity of products within an image, leading to potential inaccuracies in payment processing.
Innovation Solution
A product quantity determination apparatus and method that acquires multiple images of a target region, performs product detection processing on each image, and determines a first object detected in a predetermined number of images, excluding it from the total detected products to set the accurate product quantity for payment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If image processing is performed to detect products in a single image, then product quantity can be determined quickly, but false recognition occurs (e.g., hands recognized as products)
Solution Approach 1:
The patent applies preliminary action by capturing multiple images before final product quantity determination. The image acquisition unit captures a plurality of images of the product before the determination is made, allowing the system to pre-process and analyze multiple frames to distinguish actual products from false recognitions such as hands or arms, thereby improving reliability while maintaining productivity.
2Measurement precision
If multiple images are captured and processed, then product detection accuracy improves, but processing time and complexity increase
Solution Approach 1:
The patent merges multiple captured images into a single composite image for final product quantity determination. The image processing unit integrates information from the plurality of captured images, combining the data to enhance detection accuracy while managing processing time efficiently. This merging approach allows the system to leverage multiple frames without requiring separate processing of each individual image.
3Reliability
If general exclusion articles like hands are registered in advance, then false recognition is reduced, but the system complexity increases
Solution Approach 1:
The patent applies self-service by enabling the image processing unit to automatically distinguish and exclude false recognitions such as hands and arms through analysis of captured image data. The system performs self-verification by examining the captured images and identifying objects that should be excluded from product quantity calculations, eliminating the need for manual registration of exclusion articles and reducing system configuration complexity while maintaining high recognition accuracy.
Data Source
AI summary
A product quantity determination apparatus includes an acquisition unit, an image processing unit, and a computation unit. The acquisition unit acquires a plurality of images. The images include, in a capturing range, a target region being a region where a product may be disposed. The image processing unit performs detection processing of a product on each of the plurality of images. The computation unit determines a first product being a product detected in a predetermined number or more of the images in the detection processing, and sets, as a quantity of products to be paid for, a quantity acquired by excluding the first product from products detected by the detection processing.