Machine-Readable Code Decoding via Signal Energy Transfer
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Solution Overview
Problem
Decoding machine-readable codes such as barcodes or QR codes is prone to errors due to blurring, imaging errors, movement, noise, and brightness fluctuations, leading to incorrect evaluation of signal areas and impaired decoding accuracy.
Innovation Solution
A method that involves generating an input signal waveform from image pixels, transferring signal energy from one area to another to create a result signal waveform, which is then used for decoding, ensuring precise determination of code module positions by combining signal energies and modifying the input signal waveform to represent code modules more accurately.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional threshold-based binary conversion is used to decode machine-readable codes, then the decoding process is simple and fast, but decoding accuracy deteriorates due to blurring, noise, and brightness fluctuations causing incorrect evaluation of signal areas
Solution Approach 1:
The patent applies preliminary action by performing signal energy transfer before the actual decoding process. The method pre-processes the grayscale image by transferring signal energy from pixels with lower energy to adjacent pixels with higher energy, creating an enhanced signal representation that accounts for blurring and noise before threshold conversion and decoding occur. This preliminary enhancement improves decoding accuracy by ensuring signal areas are more accurately represented in the enhanced signal curve.
2Measurement precision
If signal areas are evaluated based on individual image pixels, then the processing is computationally efficient, but measurement precision deteriorates due to misalignment between code module boundaries and pixel edges
Solution Approach 1:
The patent applies merging by combining signal energy from multiple adjacent image pixels into a unified signal representation. The signal energy transfer process merges energy from pixels that may be partially covered by code modules, creating a consolidated signal area that better represents the actual code module boundaries. This merging approach improves measurement precision by reducing the impact of pixel-edge misalignment, as the transferred energy collectively represents the true signal area regardless of individual pixel boundaries.
3Reliability
If grayscale images are directly converted to binary images using threshold values, then the decoding process is fast, but reliability worsens due to brightness fluctuations and noise causing incorrect signal area evaluation
Solution Approach 1:
The patent introduces an intermediary step between grayscale image capture and binary conversion. The signal energy transfer process acts as an intermediary that enhances the grayscale signal before threshold conversion, creating an enhanced signal curve that more accurately represents true signal areas. This intermediary enhancement improves reliability by compensating for brightness fluctuations and noise, while the method maintains reasonable decoding speed through efficient energy transfer algorithms that avoid excessive computational overhead.
Data Source
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AI summary
The invention relates to a method for decoding a machine-readable code, comprising the machine-generated generation of an input image of the machine-readable code, wherein the input image comprises a plurality of image pixels, each with a value, and wherein the sequence of the values of the image pixels defines an input signal waveform, the input signal waveform comprising signal regions, each representing the signal energy in an associated signal region. The method comprises transferring the signal energy of at least one signal region to a second signal region, thereby generating a result signal waveform. Finally, the method comprises decoding the machine-readable code based on the result signal waveform.