2D Bar Code Decoding on Irregular Surfaces
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Two-dimensional bar codes, such as DataMatrix symbols, face challenges in direct part marking due to irregular surfaces and varying reflectivity, making it difficult to accurately decode symbols imprinted on non-flat or metallic parts with circular dots instead of square modules.
Innovation Solution
A method is employed to decode symbols from gray scale images by forming a binarized version to determine symbol margins, using a threshold surface to convert gray scale images into binary images, and constructing a grid to determine the state of modules based on periodicity analysis, allowing for efficient decoding on irregular surfaces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional binarization methods are used on gray scale images of bar codes imprinted on irregular surfaces, then the decoding process becomes complex and time-consuming, but the accuracy of locating symbol margins and determining module states deteriorates due to symbol contrast variation caused by irregular surfaces and illumination variation
Solution Approach 1:
The patent applies preliminary action by performing contour traversal and local threshold calculation before the main binarization process. The system traverses the contour of the bar code symbol first, calculates local threshold values along the contour, and uses these pre-computed thresholds to guide the subsequent binarization of the entire image, thereby simplifying the overall decoding process while maintaining high accuracy in locating symbol margins and determining module states even on irregular surfaces
2Measurement precision
If traditional binarization methods are used on gray scale images of bar codes imprinted on irregular surfaces, then the decoding process becomes complex and time-consuming, but the decoding speed and efficiency deteriorate
Solution Approach 1:
The patent applies segmentation by dividing the bar code image into distinct regions along its contour. The system segments the image by traversing the contour and calculating local threshold values for different segments, then applies binarization locally along the contour before extending to the entire image. This segmented approach maintains high decoding accuracy for module state determination while improving decoding speed by processing the image in manageable segments rather than as a single complex operation
3Area of stationary object
If bar code symbols are imprinted directly on parts with irregular surfaces or varying reflectivity, then the compact size and efficiency of two-dimensional bar codes are maintained, but the accuracy of reading and decoding deteriorates
Solution Approach 1:
The patent applies local quality by using locally adaptive thresholding along the contour of the bar code symbol. Instead of applying a single global threshold to the entire image, the system calculates local threshold values at different positions along the contour, accounting for variations in surface irregularities and illumination. This local adaptation maintains high decoding accuracy for compact two-dimensional bar codes imprinted on parts with varying reflectivity and surface characteristics
Data Source
AI summary
A two dimensional symbol is decoded by forming a binary image that includes the symbol. The binary is used to generate symbol margins for use in digitization. By using the binary image to determine the symbol margins, margins can be located efficiently and in the presence of symbol contrast variation caused by irregularities in the marked surface or light source angles. Digitization proceeds based on the determined margins.