Color-Driven Barcode Localization via YUV Segmentation

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Existing image signal processing technologies face challenges in rapidly localizing machine-readable indicia, such as 1D and 2D barcodes, within captured images, especially in environments with multiple barcodes, due to limited processing time and battery life in smartphones, requiring efficient methods to focus computation on likely areas containing indicia.

Innovation Solution

A color-driven localization approach using the YUV color space to identify and isolate yellow and orange regions associated with barcodes, employing thresholding formulas and dilation to create bounding boxes for targeted barcode decoding, and utilizing machine learning for feature extraction and classification to enhance barcode localization.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If traditional image processing methods are used to scan the entire image for barcode localization, then comprehensive detection coverage is achieved, but computational complexity and processing time increase significantly

Engineering Contradiction:

Improvebarcode localization accuracyVSAvoidcomputational complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent segments the image processing task into two distinct phases: first, color-based pre-screening to identify candidate regions containing yellow or orange colors, and second, barcode detection only within those segmented regions. This segmentation reduces the search space from the entire image to specific color-coded areas, thereby lowering computational complexity while maintaining detection accuracy

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent applies preliminary color-based filtering and region of interest identification before performing the computationally intensive barcode detection. By pre-identifying areas with yellow or orange colors using simple color thresholding, the system prepares the data in advance, so that subsequent barcode algorithms only need to process small candidate regions rather than the full image

Inventive Principle:

Principle #10Preliminary action

2Reliability

If full image analysis is performed to ensure all barcodes are detected, then detection completeness is improved, but processing time exceeds available time budget in mobile devices

Engineering Contradiction:

Improvedetection completenessVSAvoidprocessing time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The patent divides the image into color-based segments and processes only those segments that contain yellow or orange hues. This segmentation approach ensures that all barcodes located in colored regions are detected (maintaining reliability) while avoiding unnecessary processing of gray-scale or colorless areas (reducing time loss)

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent performs partial action by focusing computational resources only on regions with yellow or orange colors, which are identified as containing barcodes. This selective processing achieves sufficient detection completeness for the target application while significantly reducing the time required compared to analyzing the entire image

Inventive Principle:

Principle #16Partial or excessive action

3Reliability

If comprehensive image processing is applied to handle multiple barcodes, then all barcodes are decoded, but energy consumption exceeds battery life constraints

Engineering Contradiction:

Improvemulti-barcode detection reliabilityVSAvoidenergy consumption

Core Design Contradiction:

ReliabilityVSUse of energy by moving object

Solution Approach 1:

The patent segments the processing task by color regions, so that multiple barcodes are detected through separate color-based segmentations rather than exhaustive full-image analysis. This reduces energy consumption by limiting processing to only those regions that contain barcodes, while still achieving reliable detection of all barcodes present in the image

Inventive Principle:

Principle #1Segmentation

4Productivity

If color-based region identification is applied to focus on yellow and orange areas, then computational efficiency is improved, but false positive regions may be identified

Engineering Contradiction:

Improveprocessing efficiencyVSAvoidregion identification accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The patent uses color-based identification as a preliminary filtering step rather than a final determination. The yellow/orange color detection creates candidate regions that are then subjected to further verification through barcode detection algorithms, ensuring that processing efficiency gains do not compromise region identification accuracy

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS12124919B2Color driven localization of 1D and 2D barcodes in digital capture systems

Publication Date: 2024.10.22 DIGIMARC LLC

AI summary

The present disclosures relates to decoding machine readable indicia (e.g., a 1D or 2D barcode) in imagery, and related image processing technology. One claim recites a method of locating a barcode within imagery, comprising: converting the imagery to greyscale imagery; evaluating a plurality of blocks within the greyscale imagery, each of the plurality of blocks comprising n×m pixels, where both n and m are positive integers; for each block of the plurality of blocks, determining a value representing pixel diversity within the block; masking the greyscale imagery based on values of the plurality of blocks, in which blocks with a value below a predetermined value of pixel diversity are masked out or excluded; searching the masked, greyscale imagery to determine whether is includes a barcode represented therein. Of course, other claims and combinations are provided too.