Barcode Decoding via Gray Level Interpolation for Long-Range Reading
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Solution Overview
Problem
Barcode decoding becomes problematic when the barcode reader is far from the barcode due to the decrease in stripe and space width, leading to vague images and decreased decoding success rates, especially without a zoom lens.
Innovation Solution
The method involves capturing an image, analyzing gray level distributions to determine the distance, and interpolating missing bars or spaces based on characteristic parameters to recover the image, thereby increasing decoding success rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If the barcode reader is positioned far from the barcode to expand reading range, then the reading coverage is improved, but the image becomes vague and decoding success rate decreases
Solution Approach 1:
The patent applies preliminary action by performing interpolation processing on the barcode image before decoding. The method预先 divides the image into bar and space areas, identifies peak and valley points, and interpolates missing features before the decoding step, thereby compensating for image degradation at long distances and ensuring successful decoding
Solution Approach 2:
The patent changes parameters by dynamically adjusting the interpolation strength and gray level thresholds based on the detected distance between the barcode reader and the barcode. When the distance is large, stronger interpolation is applied; when the distance is small, minimal or no interpolation is performed. This adaptive parameter adjustment optimizes decoding success rate across different reading distances
2Length of moving object
If the distance between barcode reader and barcode increases, then the reading range is extended, but the stripe and space width decreases leading to vague images
Solution Approach 1:
The patent introduces an intermediary processing step between image capture and decoding. The interpolation module acts as a mediator that reconstructs missing bar and space features by analyzing gray level distributions and peak-valley relationships, thereby compensating for the loss of image clarity at long distances without requiring physical proximity
Solution Approach 2:
The patent creates a corrected copy of the degraded barcode image through interpolation. By generating synthetic bar and space patterns based on detected peak and valley points, the method produces a reconstructed image that replicates the original barcode structure even when the captured image is vague due to long distance
Data Source
AI summary
A barcode decoding method includes steps of analyzing a relative relationship between at least two characteristic points of a gray level distribution of a target scanning line of a target barcode to obtain at least one reference characteristic parameter; when determining a current distance between a barcode reader and the target barcode being a relatively long distance, dividing the gray level distribution into at least one bar area and at least one space area; setting a gray level region and locating at least one peak point and/or at least one valley point located within the gray level region from the gray level distribution; when the peak point is located within the bar area, interpolating a space corresponding to the peak point into the bar area; and when the valley point is located within the space area, interpolating a bar corresponding to the valley point into the space area.