Barcode Readers with 2D/3D Imaging for Object Recognition

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Solution Overview

Problem

Existing barcode readers primarily rely on two-dimensional image data for decoding and analysis, limiting their detection capabilities and performance, particularly in environments where improved detection of three-dimensional features and object recognition are necessary.

Innovation Solution

Integration of both two-dimensional and three-dimensional imaging apparatuses in barcode readers to enhance image data by correlating 3D features with 2D data, enabling improved barcode decoding, object recognition, and detection of operator actions.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If only two-dimensional imaging apparatus is used in barcode readers, then device complexity is reduced, but detection precision and object recognition capability are limited

Engineering Contradiction:
Improvedetection precisionVSAvoiddevice complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The patent combines a two-dimensional imaging apparatus and a three-dimensional imaging apparatus into a single barcode reader system. The 2D imager captures 2D image data while the 3D imager captures 3D image data, and both are processed together to enhance detection precision and enable advanced object recognition capabilities beyond what either imager could achieve alone.

Inventive Principle:
Principle #5Merging (Combining)

Solution Approach 2:

The patent introduces three-dimensional imaging capability to a traditionally two-dimensional barcode reading system. By adding the 3D imager and processing 3D image data in conjunction with 2D image data, the system transcends the limitations of 2D analysis and achieves improved detection precision for depth-aware applications.

Inventive Principle:
Principle #17Another dimension (Dimensionality change)

2Adaptability or versatility

If two-dimensional image data is used for multiple purposes including off-platter weighing and spoofing detection, then versatility is improved, but detection success rate is limited

Engineering Contradiction:
ImproveversatilityVSAvoiddetection success rate
Core Design Contradiction:
Adaptability or versatilityVSReliability

Solution Approach 1:

The patent merges 2D image data and 3D image data to perform multiple detection functions including off-platter weighing detection, spoofing detection, and barcode decoding. This combination maintains versatility while improving detection success rate by providing additional dimensional information for more reliable analysis.

Inventive Principle:
Principle #5Merging (Combining)

3Adaptability or versatility

If three-dimensional imaging apparatus is added to barcode reader, then object recognition capability is improved, but device complexity increases

Engineering Contradiction:
Improveobject recognition capabilityVSAvoiddevice complexity
Core Design Contradiction:
Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent integrates the 3D imaging apparatus with the existing 2D imaging apparatus in a unified barcode reader system. Both imagers work together with a single processor that handles both 2D and 3D image data, enabling enhanced object recognition capability while managing device complexity through integrated architecture.

Inventive Principle:
Principle #5Merging (Combining)

Data Source

PatentUS12393803B2Barcode readers with 3D camera(s)
Publication Date: 2025.08.19 ZEBRA TECHNOLOGIES CORP
  • US12393803B2 patent drawing
  • US12393803B2 patent drawing
  • US12393803B2 patent drawing

AI summary

At least some embodiments described herein are directed to a machine vision method, which involves capturing both a two-dimensional (2D) image of an object to identify a barcode and determine 3D features, and a three-dimensional (3D) image of the environment. The 3D image data is examined for the presence of the 3D object features. If a feature is missing, a digital fault detection signal is provided. If a feature is present, at least one parameter of the machine vision system is adjusted. The method also includes decoding the barcode and determining the object's orientation based on the barcode location in the 2D image.