Bioptic Barcode Reader Adaptive Imaging for Low Contrast Decoding
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Solution Overview
Problem
Traditional barcode reading systems face challenges in capturing and decoding low contrast barcodes due to fixed depth of focus and exposure time, leading to inadequate image fidelity and increased operator annoyance or reduced decoding capability when items are swiped quickly.
Innovation Solution
The system adjusts imaging parameters, such as exposure time and illumination, in response to initial decoding failures, capturing subsequent images with optimized settings to improve barcode readability and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If the aperture is decreased to maintain depth of focus, then the depth of focus is maintained, but the amount of light received by the imager decreases
Solution Approach 1:
The system dynamically adjusts the exposure time based on the detected barcode characteristics and lighting conditions. Instead of using a fixed aperture setting, the imager adapts its exposure parameters in real-time to capture sufficient light while maintaining image quality for decoding.
Solution Approach 2:
The system changes the exposure time parameter adaptively based on the specific barcode being scanned and environmental conditions. This allows the imager to optimize light capture for each scanning scenario without being constrained by a fixed aperture setting.
2Illumination intensity
If the illumination is increased to improve barcode capture, then the amount of light received increases, but operator annoyance increases
Solution Approach 1:
The system adjusts the exposure time parameter to optimize light capture without increasing illumination intensity. By extending the exposure duration, the imager collects sufficient light from ambient sources, avoiding the need for bright active illumination that would annoy operators.
Solution Approach 2:
The system uses periodic or pulsed illumination in conjunction with extended exposure times to capture barcode images. This approach provides sufficient light for imaging while minimizing continuous illumination that would cause operator discomfort.
3Illumination intensity
If the exposure time is increased to improve barcode capture, then the amount of light received increases, but the system cannot capture minimally blurred images when barcodes are swiped rapidly
Solution Approach 1:
The system dynamically adapts its exposure time based on the detected motion characteristics of the barcode. When rapid movement is detected, the system adjusts parameters to capture the image at the optimal moment, balancing exposure duration with motion blur constraints.
Solution Approach 2:
The system performs preliminary detection of barcode presence and motion characteristics before capturing the image. This allows it to pre-adjust exposure parameters to optimize for the specific scanning scenario, whether the barcode is moving slowly or being swiped rapidly.
4Stability of the object's composition
If the aperture is fixed to maintain consistent depth of focus, then the depth of focus remains stable, but the system cannot adequately capture low contrast barcodes
Solution Approach 1:
The system uses dynamic parameter adjustment where exposure time and other imaging parameters are adapted based on real-time analysis of barcode characteristics, contrast levels, and lighting conditions. This allows optimization of image fidelity for each specific scanning scenario while maintaining stable depth of focus through fixed aperture.
Data Source
AI summary
A method is disclosed for adjusting imaging parameters of a bioptic barcode reader. The method includes capturing, by an imaging assembly, an initial image of a target object having an indicia thereon. The imaging assembly captures the initial image according to an initial imaging parameter. The method further includes attempting to decode the indicia from the initial image, and responsive to being unable to decode the indicia, detecting a substantially static presence of the target object within a field of view (FOV) of the imaging assembly. The method then includes, responsive to detecting the substantially static presence of the target object within the FOV, adjusting the initial imaging parameter to a subsequent imaging parameter, wherein the subsequent imaging parameter is different than the initial imaging parameter.