Barcode Detection via Contour Analysis for Damaged Patterns
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional data reading systems face challenges in accurately detecting and processing barcodes with damaged or incomplete finder patterns, especially when they are partially obscured by nearby text or images, leading to computational inefficiencies and inaccuracies.
Innovation Solution
A data reading method that uses contour analysis and adaptive local thresholding to identify and distinguish barcodes from surrounding graphical data without relying on finder patterns, employing techniques like Canny edge detection and adaptive piecewise local thresholding to efficiently process only relevant image regions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional boundary tracking methods are used to locate barcodes, then the system works well in ideal conditions with complete finder patterns, but the system fails or becomes computationally inefficient when finder patterns are damaged or obscured by surrounding text and images
Solution Approach 1:
The patent segments the barcode detection process into multiple stages: initial contour detection to identify potential barcode regions, followed by more detailed analysis only in those segmented regions. This avoids processing the entire image and allows the system to handle damaged patterns by focusing computational resources on promising areas rather than requiring complete finder patterns throughout.
Solution Approach 2:
The patent applies partial action by implementing a multi-stage detection approach where full computational analysis is performed only on regions identified as potential barcodes in preliminary stages. This partial processing strategy maintains reliability for damaged patterns while improving computational efficiency by avoiding redundant analysis of non-barcode regions.
2Reliability
If the system processes the entire image to detect barcodes, then it can identify barcodes even with damaged finder patterns, but it creates high computational redundancies and processing inefficiencies
Solution Approach 1:
The patent performs preliminary contour detection and region identification before conducting full barcode analysis. This preliminary action identifies candidate regions that likely contain barcodes, allowing the system to maintain high detection accuracy for damaged patterns while significantly reducing processing time by limiting detailed analysis to only those pre-identified regions.
3Productivity
If conventional reading methods are used, then the system operates quickly in ideal conditions, but it lacks robustness and fails when finder patterns are incomplete or damaged
Solution Approach 1:
The patent implements a dynamic detection strategy that adapts the level of analysis based on the detected features. In ideal conditions with complete finder patterns, the system uses快速 conventional methods for high-speed reading. When damaged or incomplete patterns are detected, the system dynamically switches to more robust multi-stage contour analysis, maintaining adaptability across different barcode conditions while preserving speed when possible.
Data Source
Figure 1~2B
Figure 3A~3D
Figure 4~5B
AI summary
The disclosure relates to a data reading system and method for obtaining target data from an image. The data reading method includes obtaining an image containing the target data, and identifying a starting pixel coordinate on the image. The method further includes determining an initial local threshold value based on the selected starting pixel and analyzing the image to detect one or more high contrast boundaries or contours. After detecting the boundaries, the method includes analyzing the one or more boundaries to identify the target data in the image.