QR Code Locator Pattern Corner Detection in Noisy Scans
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Solution Overview
Problem
Existing methods struggle to accurately identify and locate QR code finder patterns in noisy or damaged images, which hinders the reliable detection and reading of QR codes.
Innovation Solution
The proposed solution involves processing scanned images to reduce noise effects by converting individual white pixels with black neighbors to black, while preserving groups of adjacent white pixels, and identifying line segments with a 1:1:3:1:1 ratio to determine the corner points of QR code locator patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If noise reduction processing is applied to scanned QR code images, then the reliability of locator pattern identification is improved, but the complexity of image processing increases
Solution Approach 1:
The patent applies noise reduction processing to the scanned image before attempting to identify locator patterns. By preprocessing the image to remove noise and damage artifacts first, the subsequent pattern recognition operates on cleaner data, improving reliability while the preprocessing steps are designed to be computationally efficient
Solution Approach 2:
The patent segments the image processing into distinct stages: noise reduction phase, locator pattern detection phase, and corner position determination phase. This segmentation allows each stage to focus on specific tasks with optimized algorithms, managing overall complexity through modular processing steps
2Object-affected harmful factors
If individual white pixels with black neighbors are converted to black to reduce noise, then noise effects are reduced, but the risk of altering valid QR code features increases
Solution Approach 1:
The patent applies different processing rules to different pixel configurations based on their local neighborhood characteristics. Individual isolated white pixels surrounded by black pixels are converted to black (treating them as noise), while groups of adjacent white pixels are preserved (treating them as valid features). This local quality differentiation allows selective noise removal while preserving legitimate QR code structure
Solution Approach 2:
The patent converts the harmful effect of noise by identifying and eliminating isolated white pixels that represent sensor errors or damage artifacts. By targeting specifically those pixels with black neighbors on all four sides, the method transforms noise reduction into a beneficial feature enhancement process rather than simple data loss
3Measurement precision
If line segment identification with 1:1:3:1:1 ratio is used to locate corners, then corner position accuracy is improved, but the difficulty of detecting and measuring increases
Solution Approach 1:
The patent uses the specific parameter of line segment length ratios (1:1:3:1:1 pattern) as a fingerprint for identifying corner positions in locator patterns. By measuring and comparing the relative lengths of consecutive black and white line segments, the system achieves precise corner location through ratio matching rather than absolute position measurement, improving accuracy while using computationally feasible operations
Data Source
AI summary
Various features relate to processing a scanned image to facilitate accurate locator pattern identification and/or detection of the corner locations of the locator pattern. In some embodiments to facilitate the identification of corner points the scanned image is processed to reduce the effect of noise and/or other damage on the subsequent location identification process. Individual white pixels which have black pixels on four sides are converted to black as part of the processing while multiple white pixels adjacent each other are left unaltered. In some embodiments processing does not alter the color of black pixels. Corner points of the locator pattern are identified through additional processing and identification of line segments satisfying an expected black, white, black, white, black segment portion ratio.