Barcode Scanner Signal-to-Noise Ratio Thresholding
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Optical bar code scanning is hindered by noise sources that can lead to false identification of peaks or failure to recognize peaks, resulting in decoding errors due to the signal-to-noise ratio being less than 1 when no object is present, and increased error probability around the transition when an object is introduced.
Innovation Solution
The system improves decoding accuracy by using information about signal and noise levels to evaluate the reliability of transitions, computing signal-to-noise ratios, and setting thresholds based on noise levels to exclude false peaks, favoring transitions with higher signal-to-noise ratios and considering the presence of error correction features and data importance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If noise filtering is applied to improve signal detection, then false peak identification is reduced, but legitimate peaks may also be filtered out
Solution Approach 1:
The patent applies different threshold criteria to different regions of the scan signal. A first threshold is used for initial peak detection, while a second, higher threshold is applied specifically at transition regions where the signal changes abruptly. This local differentiation allows the system to be more sensitive to peaks in stable regions while being more conservative in transition regions, thereby resolving the contradiction between detecting all peaks and avoiding false detections.
2Adaptability or versatility
If a lower threshold is used to detect all potential peaks, then more transitions are identified, but false peaks from noise increase
Solution Approach 1:
The patent implements dynamic threshold adjustment based on the local characteristics of the scan signal. The threshold is not fixed but adapts to the signal conditions at each point in time. When the signal exhibits characteristics of a transition (abrupt change), a higher threshold is applied. When the signal is stable, a lower threshold is used. This dynamic approach allows the system to maintain high sensitivity where needed while preserving noise rejection where applicable.
3Area of stationary object
If multiple scan lines are used to transect the bar code, then scanning coverage is improved, but the probability of encountering noise and errors increases
Solution Approach 1:
The patent employs a feedback mechanism where the quality of each scan line is evaluated based on the number and characteristics of detected peaks. Scan lines that exhibit excessive noise or fail to detect the expected number of transitions are identified as poor quality. The system then uses this feedback to weight or discard results from problematic scan lines, ensuring that the final bar code interpretation is based primarily on high-quality data while still benefiting from the expanded coverage provided by multiple scan lines.
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 enhances decoding accuracy by effectively distinguishing between actual transitions and noise-induced false transitions, improving the reliability of data interpretation and reducing errors in bar code scanning.
Implementation Method 1
A laser source emits a laser beam, which is reflected from a first mirror, a rotating component, and a second mirror, through a scan window to a bar code on an object. Light reflected from the bar code is returned through the scan window to a photodetector, which produces a scan signal.
Data Source
AI summary
Systems and techniques for using signal to noise ratio information to enhance bar code scanning accuracy. Noise information affecting bar code scanning operations is stored and a scan signal is monitored. Upon detection of a scan of a bar code, the signal strength of the scan signal is evaluated and signal to noise ratio values are computed. Signal to noise ratio information is used to favor or disfavor candidate decoding results. In addition, signal to noise ratio thresholds are set according to appropriate criteria. Decoding results are evaluated using the signal to noise ratio thresholds and accepted or rejected depending on whether the thresholds are met. In addition, thresholds for recognition of transitions based on peaks may be set based on expected noise affecting the scan signal, and allowed or excluded based on whether a rise from a negative peak, or fall from a positive peak, meets the threshold.