Barcode Reading via Binary Width Calculation Across Image Scales
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Solution Overview
Problem
Existing systems struggle to accurately read barcodes independently of image resolution or scale, leading to errors in interpreting barcode dimensions and data.
Innovation Solution
A system and method that converts scanned barcode images into binary data, calculates widths of bars and spaces using specific equations, and applies scaling factors based on predetermined barcode standards to adjust dimensions accurately.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If barcode reading systems use fixed image resolution processing, then processing speed is maintained, but measurement accuracy deteriorates when image scale varies
Solution Approach 1:
The system performs preliminary actions by calculating the actual physical dimensions of bars and spaces directly from the captured image using known scanner-to-item distance and scanner field of view parameters, before proceeding to barcode decoding. This preliminary dimension calculation establishes a scaling reference that enables accurate measurement regardless of image resolution, resolving the contradiction by preparing the necessary geometric information in advance.
Solution Approach 2:
The system changes the processing approach from fixed-resolution pixel-based measurement to parameter-based physical dimension calculation. By using scanner distance and field of view parameters to compute actual bar and space widths in real-world units, the system achieves measurement accuracy that is independent of image resolution or scale variations, thereby improving measurement precision without proportionally increasing complexity.
2Measurement precision
If the system calculates scaling factors based on barcode standards, then measurement accuracy improves, but processing time increases
Solution Approach 1:
The system performs preliminary calculation of bar and space widths using scanner parameters before decoding, establishing accurate physical dimensions in advance. This allows the subsequent decoding process to use pre-calculated scaling factors rather than computing them during decoding, thereby minimizing additional processing time while maintaining high measurement accuracy.
Solution Approach 2:
The system replaces traditional mechanical or empirical scaling methods with direct geometric calculation based on scanner parameters (distance and field of view). This substitution enables rapid computation of accurate dimensions through mathematical formulas rather than iterative adjustment or physical measurement, improving precision without significant time penalty.
3Adaptability or versatility
If the system processes barcodes at varying scales, then versatility improves, but measurement reliability deteriorates
Solution Approach 1:
The system uses parameter-based calculation (scanner distance and field of view) to determine actual bar and space widths, making the measurement process independent of image scale or resolution. This approach maintains reliable and consistent dimension measurements whether the barcode is captured at close range or distance, thereby ensuring measurement reliability across varying scales and distances.
Solution Approach 2:
The system achieves universal applicability by using a unified geometric calculation method that works regardless of barcode size, distance, or image resolution. The same scanner parameters and calculation formulas apply whether reading a small barcode nearby or a large barcode at distance, enabling the system to handle diverse barcode scenarios reliably without requiring separate processing paths.
Data Source
AI summary
The present disclosure relates to a system for reading a barcode independently of image resolution or scale of a captured barcode image. In one embodiment, the system includes an optical sensor and a processor. The optical scanner can scan a barcode, including a plurality of bars and spaces, into a scanned image. The processor can convert the scanned image into binary data. The processor can also calculate numbers of ones (1s) between zeros (0s) in the binary data and determine widths of one of i) each of the bars and ii) each of the spaces based on the calculated numbers of ones (1s). The processor can further calculate numbers of zeros (0s) between ones (1s) in the binary data and determine widths of the other one of i) each of the bars and ii) each of the spaces based on the calculated numbers of zeros (0s).