Distance Map Decoding for Barcode Reader Working Range
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Solution Overview
Problem
Conventional optical scanning systems face challenges in decoding barcodes at varying distances due to limited working ranges and the need for cumbersome manual adjustments, and existing digital solutions are slow and power-intensive.
Innovation Solution
An optical reader system that uses a lens system and optical sensor to focus encoded characters, generating a distance map with seed codewords and values to quickly identify candidate characters by comparing them to a subset of valid characters within a specified range, reducing decode time and power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Length of stationary object
If conventional optical scanning systems are used to read barcodes at greater distances, then the working range is limited, but adding motorized systems with additional lenses or mirrors increases device complexity and cost
Solution Approach 1:
The patent segments the decoding process by creating distance maps that divide the code space into regions based on distance from a seed codeword. This allows the system to handle different distance ranges separately, improving working range without adding complex motorized components.
Solution Approach 2:
The patent performs preliminary action by pre-computing distance maps and organizing codewords into distance-based bins before actual decoding occurs. This pre-processing enables faster decoding at various distances without requiring real-time complex adjustments.
2Reliability
If digital circuits are used to analyze and identify barcode characters from noisy or weak signals, then decoding accuracy improves, but processing speed becomes slow due to the enormous number of iterations required
Solution Approach 1:
The patent segments the search space by organizing codewords into distance-based bins. Instead of checking all possible codewords, the system only searches within the relevant distance bin, dramatically reducing the number of iterations needed while maintaining decoding accuracy.
Solution Approach 2:
The patent applies local quality by focusing computational resources on the specific distance region where the barcode is likely located. By using distance maps to identify the relevant bin, the system concentrates processing power where it's most needed rather than uniformly searching the entire code space.
3Reliability
If the representation of the barcode symbol is out of focus or at extreme distances, then decoding becomes challenging, but manual movement of the symbol or scanner is cumbersome and may not be possible
Solution Approach 1:
The patent changes the parameter space by transforming the decoding problem from direct pattern matching to distance-based search. By computing distance metrics and using pre-generated distance maps, the system can reliably decode barcodes at various distances and focus conditions without requiring manual adjustment.
Solution Approach 2:
The patent introduces distance maps as an intermediary data structure that mediates between the received barcode signal and the code book. This intermediary enables the system to handle out-of-focus and distant representations by providing a distance-based search mechanism that is more robust to variations in quality.
4Reliability
If analog circuits are used to analyze incoming signals and segregate barcode characters from noise, then decoding capability improves, but the circuits become bulky and consume excessive power
Solution Approach 1:
The patent replaces complex analog signal processing circuits with a digital algorithmic approach using distance maps and bin-based search. This substitution eliminates the need for bulky analog circuits while maintaining decoding capability, and significantly reduces power consumption by leveraging efficient digital computation.
Solution Approach 2:
The patent segments the decoding task into distance-based bins, allowing the system to process only relevant portions of the code space. This segmentation reduces the computational burden and power consumption compared to exhaustive search methods, while maintaining the ability to segregate barcode characters from noise.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach significantly reduces decode time by limiting comparisons to a subset of characters, improving decoding speed and efficiency while minimizing power usage, with potential decoding speed improvements of up to 8 times and power savings.
Implementation Method 1
a lens system for focusing an illuminated encoded candidate character at a plane of focus
Implementation Method 2
The optical sensor includes as an input the detected light intensity corresponding to the illumination reflected from the encoded candidate character, and further includes as an output an electrical signal encoding information representative of the encoded candidate character
Data Source
AI summary
A method for decoding an encoded candidate character of a symbology is provided that includes the steps of providing a plurality of valid barcode characters of a symbology having n elements, generating a seed codeword comprising n elements, computing a seed distance value from the seed codeword to each character in the symbology, generating a distance map comprising each character in the symbology and the associated computed seed distance value, and arranging the plurality of seed distance values into a plurality of bins. Each bin contains a subset of the characters in the symbology. The method includes the steps of selecting a candidate barcode character for decoding, computing a candidate distance value from the candidate barcode character to the seed codeword, identifying the bin containing the candidate distance value, and comparing the candidate barcode character with the valid barcode characters in the bin having the candidate distance value.