Barcode Reader Imaging Non-Barcoded Products
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Solution Overview
Problem
Imaging-based bar code readers struggle to identify non-barcoded products, such as screws, nuts, and fruits, as they cannot capture the necessary measurements and features required for accurate identification, leading to time-consuming manual entry and potential errors in retail settings.
Innovation Solution
A multi-camera bar code reader system with a housing and transparent windows that captures images of both bar codes and non-barcoded items, using an image processing system to decode bar codes and determine features of non-barcoded objects by measuring dimensions and comparing shapes with a database, facilitated by a CCD or CMOS sensor array and illumination system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a traditional bar code reader is used, then bar codes can be decoded efficiently, but non-barcoded products cannot be identified
Solution Approach 1:
The imaging-based scanner is designed to perform multiple functions: it can decode bar codes when present and simultaneously measure physical dimensions and features when bar codes are absent. The system uses a single imaging device to capture images that are then processed differently based on the presence or absence of bar code patterns, enabling universal product identification across diverse product types.
Solution Approach 2:
The system changes the approach from decoding optical patterns (bar codes) to measuring physical parameters (dimensions, shape, color). By detecting the absence of bar code patterns and switching to parameter-based measurement mode, the system adapts its identification methodology based on the state of the target object.
2Reliability
If manual identification and entry is used for non-barcoded products, then product identification can be achieved, but time consumption increases and errors occur
Solution Approach 1:
The system enables self-service identification by automatically capturing images, analyzing product features, measuring dimensions, and determining product identity without requiring clerk intervention. The imaging-based scanner performs the entire identification process autonomously, eliminating manual entry and reducing both time consumption and human error.
Solution Approach 2:
The patent replaces the manual mechanical process of visual comparison and keyboard entry with an automated optical imaging and digital processing system. The imaging-based scanner uses cameras and image processing algorithms to substitute human clerks in the product identification task, significantly improving both speed and accuracy.
3Loss of information
If imaging-based scanning is attempted for non-barcoded products, then product images can be captured, but accurate identification cannot be achieved without bar codes
Solution Approach 1:
The system transitions from two-dimensional bar code pattern recognition to three-dimensional physical measurement by capturing and analyzing multiple dimensional attributes including length, width, height, shape, and color. This dimensional expansion provides sufficient information for product identification when bar codes are absent.
Solution Approach 2:
The patent introduces image processing software and measurement algorithms as intermediaries between the captured product image and the final identification. These computational tools extract meaningful features from raw images, measure physical dimensions, and match products against database entries, bridging the gap between visual capture and accurate identification.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables efficient and accurate identification of both barcoded and non-barcoded items, reducing manual entry errors and improving checkout efficiency by providing precise measurements and features for items like screws and fruits, ensuring correct SKU entry and product recognition.
Implementation Method 1
a camera having an image capture sensor array positioned within the housing interior region for capturing an image of a bar code within a camera field of view
Data Source
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AI summary
The present disclosure concerns a bar code reader 10 that can both interpret bar codes and determine a feature of a target object 230 not having a bar code affixed thereto. The bar code reader includes a housing including one or more transparent windows H, V and defining a housing interior region. As a target object is swiped or presented in relation to the transparent windows an image of the target object is captured. A camera C1 - C6 has an image capture sensor array positioned within the housing interior region for capturing an image of a bar code within a camera field of view. An image processing system has a processor for decoding a bar code carried by the target object. If the target object has no bar code, the image processing system determines a feature such as a dimension of the target object from images captured by the imaging system.