Barcode Detection Using Blob Clustering and Hough Transformation

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Solution Overview

Problem

Existing barcode detection technologies suffer from high false positive rates, leading to miss-detection of barcodes, especially in real-time applications using mobile devices where noise and distortion are prevalent.

Innovation Solution

A method involving blob detection, imaginary line clustering, and feature vector projection in a Cartesian coordinate system to group blobs into rectangular shapes corresponding to barcodes, using Hough transformation and filtering to improve recognition accuracy and reduce noise.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If Hough transformation is used for detection of bars in barcode, then bar recognition capability is improved, but false positive rate increases leading to miss-detection

Engineering Contradiction:

Improvebar recognition capabilityVSAvoidfalse positive rate

Core Design Contradiction:

Measurement precisionVSReliability

Solution Approach 1:

The patent segments the barcode detection process into multiple stages: initial bar detection using Hough transformation, followed by clustering analysis of detected bars, and final verification. This segmentation allows the system to use Hough transformation for its strength in bar recognition while adding subsequent steps to filter false positives, thereby resolving the contradiction between recognition capability and reliability.

Inventive Principle:

Principle #1Segmentation

2Measurement precision

If sophisticated barcode laser reader is used, then barcode reading accuracy is improved, but device complexity and cost increase

Engineering Contradiction:

Improvebarcode reading accuracyVSAvoiddevice complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent replaces the mechanical/optical sophisticated barcode laser reader system with a computational approach using standard mobile device cameras and image processing algorithms. By substituting hardware complexity with software-based blob detection, Hough transformation, and clustering methods, the system achieves comparable accuracy while using simple, widely available mobile device components.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Productivity

If real-time barcode detection is implemented on mobile devices, then detection speed is improved, but detection accuracy decreases due to noise and distortion

Engineering Contradiction:

Improvedetection speedVSAvoiddetection accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The patent applies preliminary filtering and preprocessing steps before main detection algorithms. Blob detection identifies candidate regions first, followed by Hough transformation only on these candidates rather than the entire image. This preliminary action reduces computational load for real-time processing while maintaining accuracy by focusing resources on relevant regions, thus resolving the speed-accuracy trade-off.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS9818012B2Method for barcode detection, barcode detection system, and program therefor

Publication Date: 2017.11.14 INTERNATIONAL BUSINESS MACHINE CORPORATION

AI summary

A method for barcode detection, barcode detection system and program. In method for detecting a barcode, an information processing apparatus executes the steps of: detecting a plurality of blobs from an image; for each detected blob, obtaining imaginary lines bisecting the detected blob perpendicular at the middle of the detected blob, determining at least one cluster of the imaginary lines in a feature space according to slopes and positions of the imaginary lines and grouping the blobs in one cluster to a rectangular shape corresponding to the barcode.