QR Code Decoding with Damaged Position Detection Pattern
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Solution Overview
Problem
Conventional methods for decoding QR codes with damaged position detection patterns are inefficient and prone to errors, particularly when only one detection pattern is damaged, as they require complex reconstruction processes and may misidentify correction patterns.
Innovation Solution
A decoding method and system that binarizes the QR code image, searches for position detection patterns, determines their positional relation, and uses location patterns to accurately partition the QR code region, allowing for efficient decoding with reduced errors by judging the geometrical and black/white pattern characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional reconstruction methods are used for QR codes with damaged position detection patterns, then the QR code can be decoded, but the process is complex and reconstruction efficiency is low
Solution Approach 1:
The patent segments the QR code into functional regions (position detection patterns, alignment patterns, timing patterns, data regions) and analyzes their geometric relationships. By dividing the recognition process into distinct steps (detecting two intact position detection patterns, determining their spatial relationship, locating the damaged pattern based on geometric constraints), the method achieves efficient reconstruction without complex overall processing
Solution Approach 2:
The patent performs preliminary detection of two intact position detection patterns and establishes their geometric relationship before attempting to locate the damaged pattern. By pre-determining the spatial configuration and using the timing patterns as reference, the system prepares the necessary geometric constraints in advance, enabling direct calculation of the damaged pattern's location without iterative reconstruction
2Reliability
If conventional reconstruction methods are used for QR codes with damaged position detection patterns, then the QR code can be decoded, but the process involves redundant operations and misidentification of correction patterns
Solution Approach 1:
The patent applies different recognition strategies to different regions of the QR code. Position detection patterns are identified by their specific geometric characteristics (square shape, size, position), while alignment patterns and timing patterns are recognized by their distinct local structures. This region-specific approach enables accurate differentiation between pattern types and avoids misidentification
Solution Approach 2:
Instead of attempting to reconstruct the damaged position detection pattern by guessing or using complex algorithms, the patent inverts the approach: it uses the two intact position detection patterns and the known geometric constraints of QR code structure to directly calculate where the damaged pattern should be located. This inverse calculation method simplifies the process and eliminates redundant operations
3Measurement precision
If the QR code is partitioned with grids according to position detection patterns and location pattern, then decoding accuracy is improved, but additional processing steps are required
Solution Approach 1:
The patent performs preliminary grid partitioning of the QR code image based on the detected position detection patterns and timing patterns before decoding. By establishing the grid structure in advance using the geometric relationships of the detected patterns, the system prepares the data for accurate decoding without requiring complex real-time adjustments during the decoding process
Data Source
AI summary
The invention provides a decoding method and system for a QR code with one damaged position detection pattern. The decoding method comprises the steps: binarizing a received image containing a QR code pattern and searching for position detection patterns, decoding the QR code pattern through the following method if two position detection patterns are searched out, recording the linear equations of the boundaries of the two position detection patterns and the vertex coordinates of the two position detection patterns and calculating the data bit width of the QR code pattern, searching out a location pattern between the two position detection patterns with the positional relation determined, determining the region where the QR code pattern is located according to the two position detection patterns and the location pattern, partitioning the region where the QR code pattern is located with grids, and decoding the QR code pattern partitioned with grids.