One-Dimensional Optical Code Reading via Sharpened Grayscale Binarization

Solution Overview

Problem

Existing barcode reading technologies face challenges in accurately binarizing grayscale image data due to interfering effects such as blurring, noise, and varying code quality, leading to inadequate decoding results.

Innovation Solution

A method for reading one-dimensional optical codes involves capturing image data, generating sharpened grayscale value profiles with increased resolution and sharper edges, and then binarizing these profiles to form black-and-white profiles for successful code reading. This process can utilize machine-learning methods, such as convolutional neural networks, or classic methods like Richardson-Lucy deconvolution.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If conventional binarization methods (threshold value method, differential method) are used to convert grayscale values to black-and-white values, then the decoding process can proceed, but the binarization quality becomes inadequate under interfering effects such as blurring, noise, and low contrast

Engineering Contradiction:

Improvebinarization qualityVSAvoidinterfering effects (blurring, noise, low contrast)

Core Design Contradiction:

ReliabilityVSObject-affected harmful factors

Solution Approach 1:

The patent applies deblurring and sharpening operations as preliminary actions before binarization. The grayscale image is first deblurred using deconvolution or other deblurring techniques, then sharpened using edge detection or sharpening filters. This preliminary enhancement of the grayscale image ensures that subsequent binarization produces higher quality binary images even under interfering effects like motion blur and low contrast.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent introduces an intermediary processing stage between image capture and binarization. Instead of directly binarizing the raw grayscale image, the system first processes it through deblurring and sharpening operations. This intermediary enhancement stage acts as a mediator that prepares the image data to withstand the harmful effects of blurring and noise during the final binarization step.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Adaptability or versatility

If multiple binarization algorithms are executed in parallel to handle different problem cases, then more problem situations can be addressed, but the processing complexity and computational load increase significantly

Engineering Contradiction:

Improveability to handle different problem casesVSAvoidprocessing complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent changes the parameters of the single binarization algorithm by first modifying the grayscale image parameters through deblurring and sharpening operations. Instead of changing the binarization algorithm itself to handle different cases, the system changes the input image parameters (sharpness, contrast, focus) through preliminary processing, allowing a single binarization algorithm to effectively handle various problem cases.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent extracts and addresses the interfering effects (blurring, noise, low contrast) as separate problems to be solved before binarization. By taking out the deblurring and sharpening operations as distinct preliminary steps, the system handles these harmful factors individually before applying the binarization algorithm, thereby simplifying the overall processing approach compared to running multiple binarization algorithms in parallel.

Inventive Principle:

Principle #2Taking out (Extraction)

3Productivity

If the grayscale image is directly binarized without preliminary processing, then the processing speed is faster, but the reading success rate decreases for low-resolution and blurred codes

Engineering Contradiction:

Improveprocessing speedVSAvoidreading success rate

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The patent applies deblurring and sharpening operations as preliminary actions before binarization. The grayscale image is first deblurred using deconvolution or other deblurring techniques, then sharpened using edge detection or sharpening filters. This preliminary enhancement of the grayscale image ensures that subsequent binarization produces higher quality binary images even under interfering effects like motion blur and low contrast.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent introduces an intermediary processing stage between image capture and binarization. Instead of directly binarizing the raw grayscale image, the system first processes it through deblurring and sharpening operations. This intermediary enhancement stage acts as a mediator that prepares the image data to withstand the harmful effects of blurring and noise during the final binarization step.

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS12307755B2Reading a one-dimensional optical code using a black-and-white profile formed from grayscale value profiles

Publication Date: 2025.05.20 SICK AG

AI summary

A method for reading a one-dimensional optical code, wherein image data including the code are captured and a plurality of grayscale value profiles through the code are obtained from the image data, a black-and-white profile is formed from the grayscale value profiles by binarization, and the code content of the code is read from the black-and-white profile, wherein, for preparing the binarization, a sharpened grayscale value profile is first generated from the plurality of grayscale value profiles, the sharpened grayscale value profile having, as compared to the original image data, increased resolution, sharper edges, and more pronounced extrema, and the sharpened grayscale value profile is binarized to form the black-and-white profile.