Barcode Scaling Mechanism with Dot Gain Erosion
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Solution Overview
Problem
Printed barcodes converted to different DPI densities face issues with readability due to dot gain and scaling methods, resulting in distorted bar and space sizes, poor readability, and variability in bar sizes.
Innovation Solution
The method involves upscaling the image, eroding it to compensate for dot gain, and then scaling it to the desired size using nearest neighbor scaling for integer factors and area scaling for minimal distortion, preserving the centroid and gray bar information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If dot gain compensation is performed by removing pels from binary barcode data, then dot gain is compensated, but barcode readability deteriorates due to coarse removal and subsequent distortion
Solution Approach 1:
The patent applies preliminary action by performing erosion (dot gain compensation) on the image at the original DPI before converting to the target DPI. This sequence ensures that the compensation is applied to the original binary data structure, and then the erosion operation refines the bar widths to account for dot gain without causing the distortion that occurs when compensation is attempted after DPI conversion.
Solution Approach 2:
The patent replaces the coarse pel removal mechanism with a morphological erosion operation. Instead of simply removing discrete pels from binary data, the erosion operation smoothly reduces bar widths while maintaining the overall structure, and this is followed by a sophisticated scaling algorithm that preserves readability by considering both bar and space dimensions.
2Ease of manufacture
If nearest neighbor scaling is used to convert barcode data to different DPI, then conversion is simple, but barcode readability deteriorates due to distortion of bars and spaces
Solution Approach 1:
The patent replaces the simple nearest neighbor scaling mechanism with a sophisticated scaling algorithm that processes both bar and space dimensions simultaneously. The new scaling method calculates target widths and spaces based on the desired DPI ratio, then applies these dimensions systematically across the entire barcode, preserving the binary structure and readability while achieving the required DPI conversion.
Solution Approach 2:
The patent changes the scaling parameters by introducing separate control for bar and space dimensions based on the target DPI ratio. Instead of uniform pixel replication, the scaling operation uses calculated width ratios to determine the precise dimensions of each bar and space element, ensuring that the binary encoding structure is maintained at the new DPI while optimizing readability.
3Measurement precision
If bar code width is increased to make wide elements more distinguishable, then scanner distinction improves, but bar code size increases and compactness is lost
Solution Approach 1:
The patent changes the width parameter of bars based on the target DPI ratio. When converting to a higher DPI, the algorithm calculates appropriate width reductions to maintain the binary encoding while improving distinguishability. When converting to lower DPI, it adjusts widths to prevent excessive thinning. This dynamic parameter adjustment optimizes both scanner distinction and barcode compactness for each target DPI.
Solution Approach 2:
The patent applies preliminary anti-action by pre-calculating the appropriate bar widths and spaces before generating the final barcode at the target DPI. The algorithm anticipates the readability requirements of the target resolution and adjusts the dimensions accordingly, preventing the need for post-processing corrections and ensuring optimal scanner distinction from the outset.
Data Source
AI summary
A method is disclosed. The method includes receiving an image, upsampling the image, eroding the upsampled image to compensate for dot gain and scaling the eroded image to scale the image to a desired size.