Barcode Reader Image Quality via 2D Module Matching
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Solution Overview
Problem
Existing imaging-based barcode readers often capture blurred images when the reader or the target object is moving, even if the barcode is accurately decoded, due to the inability to maintain image quality during relative motion.
Innovation Solution
The system employs a 2D barcode with a unit module size matching the smallest feature to be preserved, and a controller that confirms image suitability by evaluating indicia within the field of view, storing the image and using multiple 2D barcodes to ensure clear imaging without blurring, even during movement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the bar code reader or target object moves during image capture, then the barcode can be decoded, but the image quality becomes blurred
Solution Approach 1:
The patent segments the imaging process into two distinct functions: (1) capturing the barcode for decoding purposes, and (2) capturing the surrounding document image for quality assessment. The barcode region is processed separately for decoding while the document region is evaluated for blur, allowing the system to accept blurred barcode images as long as the document regions remain clear.
Solution Approach 2:
The patent applies different quality standards to different regions of the image. The barcode region can tolerate some blur while the document regions (margins, headers, footers) must remain sharp. This local quality approach allows selective evaluation where only critical document regions are assessed for image quality, not the entire image uniformly.
2Loss of substance
If only the barcode region is captured to reduce output size, then the image data volume decreases, but the ability to assess overall image quality is limited
Solution Approach 1:
The patent extracts specific document regions (margins, headers, footers) from the full image for quality assessment purposes. Instead of analyzing the entire image or only the barcode region, it selectively extracts and evaluates these peripheral document regions which are less critical for decoding but valuable for quality assessment.
Solution Approach 2:
The patent performs preliminary quality assessment on extracted document regions before final image processing or transmission. By evaluating these regions in advance, the system can determine whether the captured image meets quality standards without needing to process or transmit the entire high-resolution image.
3Measurement precision
If multiple images are captured to ensure quality, then the image quality increases, but the time required for capture and processing increases
Solution Approach 1:
The patent applies partial action by evaluating only specific document regions rather than the entire image for quality assessment. This selective evaluation requires less processing time while still providing sufficient quality metrics to determine whether the captured image is acceptable for its intended use.
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 ensures that images are captured and decoded without blurring, even when the reader or object is moving, by using a 2D barcode and advanced image processing techniques to maintain image quality and accuracy.
Implementation Method 1
The scan engine also typically includes an illumination system having light emitting diodes (LEDs) or a cold cathode fluorescent lamp (CCFL) that directs illumination toward a target object, e.g., a target bar code. Light reflected from the target bar code is focused through a lens located near or on the scan engine by an imaging system such that focused light is concentrated onto the pixel array of photosensitive elements.
Data Source
AI summary
The exemplary system requires a 2D barcode be located on an object, a portion of which is to be captured in an image. The module size of the 2D barcode is chosen to match the smallest feature to be preserved on the output image. While the target is moving with respect to the imager the 2D bar code is also moving and the resulting image is degraded. The imager will properly decode the 2D barcode only if the bar code is stationary (or moving very slowly) and hence will provide an acceptable image in the region of the 2D bar code.