Frequency Domain Barcode Detection via Fourier Transform

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Solution Overview

Problem

Existing methods for decoding one-dimensional and two-dimensional barcodes on two-dimensional images are inefficient due to the need for spatial domain analysis, which is time-consuming and challenging for determining barcode location, orientation, and symbology.

Innovation Solution

Converting the two-dimensional source image into a frequency domain image through discrete Fourier transforms to analyze frequency trends, allowing for quick detection of barcode presence, location, orientation, size, and symbology by identifying patterns of pixel transitions.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If spatial domain analysis is used to detect and decode barcodes, then the ability to detect and decode one-dimensional and two-dimensional barcodes is provided, but the time required to detect and decode a barcode is excessive

Engineering Contradiction:

Improvebarcode detection and decoding speedVSAvoidtime required for barcode analysis

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The patent transforms the barcode detection problem from spatial domain to frequency domain by applying Fourier transform. This parameter change in the analysis domain allows for faster identification of barcode characteristics through frequency pattern recognition, directly resolving the time consumption issue while maintaining detection accuracy

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent replaces the conventional spatial domain analysis mechanism with a frequency domain analysis mechanism. By substituting the analytical approach from spatial pixel value examination to frequency spectrum analysis, the system achieves faster barcode detection and decoding without sacrificing the ability to identify barcode presence, location, orientation, and symbology

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

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

This approach significantly reduces the time required to detect and decode barcodes by efficiently identifying barcode characteristics through frequency domain analysis, enabling faster and more accurate processing.

Implementation Method 1

Frequency domain images (FDIs) are created by performing discrete Fourier transforms on the row and column information of a two-dimensional source image

Methodology Applied

Scientific EffectFourier transform:

Data Source

PatentUS7451931B2Detecting barcodes on two-dimensional images using frequency domain data

Publication Date: 2008.11.18 INTERMEC IP CORP

AI summary

A system and method of detecting a barcode involves obtaining a two-dimensional source image and converting it into a frequency domain image (FDI). Frequency trends in the FDI are then analyzed to determine whether barcode information is present in the FDI. In this way, the presence, location, orientation, size and symbology of a barcode can be quickly and accurately determined.