Barcode Scanner Signal Segmentation for Blurred Code Decoding
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Solution Overview
Problem
Existing barcode scanning technologies face challenges in reading and processing barcodes due to issues like blurry or damaged barcodes, distance limitations, and ambient light distortion, which can lead to failed decoding and loss of inventory control benefits.
Innovation Solution
A method and system that utilize a barcode scanner with a CPU to segment and analyze input signals from a barcode, employing a scanning engine, differentiator, and integrator to generate a decodable signal, reducing noise and dynamic range requirements through segmentation and integration algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Length of stationary object
If the barcode reader cannot be placed close enough to the barcode, then the reading distance is limited, but placing it closer is needed to obtain a sharp image
Solution Approach 1:
The input signal is divided into a predetermined number of segments, with each segment containing multiple samples. This segmentation allows the system to process different portions of the signal independently, improving the ability to locate the barcode even when the image quality is degraded due to distance.
Solution Approach 2:
The patent uses an intermediary processing approach where the signal is divided into segments and representative samples are selected from each segment. This intermediary representation helps bridge the gap between distant reading and sharp image acquisition by processing the signal in a way that preserves barcode location information even when the original image quality is poor.
2Measurement precision
If the barcode image is not sufficiently sharp or damaged, then decoding accuracy decreases, but the barcode may still need to be read under these conditions
Solution Approach 1:
The system performs preliminary actions by dividing the signal into segments and selecting representative samples before the actual decoding process. This preliminary segmentation and sample selection prepares the data in a way that maintains decoding accuracy even when the original barcode image is blurry or damaged.
Solution Approach 2:
The patent changes the parameter representation of the signal by selecting at least one representative sample from each segment to determine barcode location. This parameter transformation allows the system to maintain decoding accuracy under various image quality conditions by working with processed signal representations rather than raw pixel data.
3Measurement precision
If high-end digitizers and powerful processors are used, then decoding accuracy improves, but system cost and complexity increase
Solution Approach 1:
The patent extracts only the essential information needed for barcode location by selecting at least one representative sample from each segment. This extraction approach achieves accurate decoding without requiring high-end digitizers or powerful processors, as the system processes only the critical signal portions rather than the entire high-resolution image.
Solution Approach 2:
Instead of relying on expensive, high-end digitizers and processors, the patent uses a simpler, more economical approach by processing segmented signal samples. This disposable-like approach processes only the necessary signal portions efficiently, reducing system complexity and cost while maintaining decoding accuracy.
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 enables efficient processing and decoding of noisy and blurred barcodes, reducing the need for high-end digitizers and powerful processors, and extends the reading range of scanners by accurately locating and decoding barcodes in various environments.
Implementation Method 1
receiving an input signal corresponding to a reflection of light from a bar code
Data Source
AI summary
Described is a method and system for barcode decoding. The method comprises receiving an input signal corresponding to a reflection of light from a bar code. The input signal is divided into a predetermined number of segments. Each segment includes a plurality of samples. Each of the segments is represented using at least one of the samples therefrom. At least one sample from each segment is analyzed to determine a location the bar code within the input signal.