Handheld Scanner Variable Focus for Blur-Gated Barcode Decoding
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Solution Overview
Problem
Barcode reading systems often capture blurry images due to aiming and focusing errors, leading to inefficient resource usage, time wastage, and bandwidth consumption as decode modules fail to decode obscured barcode data.
Innovation Solution
A variable focus imaging system that includes an imaging assembly and an aiming assembly, utilizing imaging processors to analyze images for blurriness and adjust focus parameters dynamically to ensure clear image capture and transmission to a decode module.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the imaging assembly captures images without blur detection, then the decode module receives images for processing, but resource waste increases due to failed decoding of blurry images
Solution Approach 1:
The imaging processor performs preliminary blur detection on captured images before transmitting them to the decode module. This preliminary action filters out blurry images that would certainly fail to decode, preventing wasted resources on futile decoding attempts and improving overall system efficiency.
2Productivity
If the imaging assembly transmits all captured images to the decode module, then the decode module has images to process, but time is wasted on decoding blurry images
Solution Approach 1:
Blur detection is performed as a preliminary step before image transmission to the decode module. This ensures that only potentially decodable clear images are sent for processing, eliminating time waste on decoding operations that would inevitably fail due to blur.
Solution Approach 2:
The imaging processor provides feedback about image quality (blurriness assessment) to control the transmission decision. This feedback mechanism allows the system to adaptively select which images to transmit based on their suitability for decoding, optimizing both time and resource utilization.
3Productivity
If the imaging assembly transmits all captured images to the decode module, then the decode module can process images, but bandwidth is consumed on transmitting blurry images
Solution Approach 1:
The imaging processor extracts and removes blurry images from the transmission pipeline before they reach the decode module. By taking out only the unsuitable blurry images rather than transmitting all images, the system reduces unnecessary bandwidth consumption while preserving the capability to process clear images effectively.
4Device complexity
If the imaging assembly uses fixed focus, then the device complexity is low, but image quality deteriorates due to aiming and focusing errors
Solution Approach 1:
The system transitions from a fixed focus mechanism to a dynamic focus adjustment system. The imaging processor analyzes image blur levels and automatically adjusts the focus parameter of the imaging assembly in response to detected blurriness, enabling the system to adapt to varying conditions and maintain high image quality without excessive complexity.
Solution Approach 2:
The focus parameter of the imaging assembly is changed dynamically based on the detected blurriness level. By adjusting this critical parameter in response to image quality assessment, the system optimizes focus accuracy for different scenarios while maintaining manageable device complexity through algorithmic control rather than mechanical complexity.
Data Source
AI summary
Imaging devices, systems, and methods for capturing and processing images for vision applications in a non-fixed environment are described herein. An example system includes: an imaging assembly, an aiming assembly, and one or more imaging processors configured to: (a) receive a first image; (b) analyze at least a portion of the first image to determine a first focus value; (c) configure a focus parameter of the imaging assembly based on the first focus value; (d) receive a subsequent image; (e) determine a blurriness value for at least a portion of the subsequent image; (f) responsive to the blurriness value being less than a predetermined threshold value, transmit the subsequent image to a decode module; and (g) responsive to the blurriness value exceeding the predetermined threshold value: determine a subsequent focus value; (ii) configure the focus parameter based on the subsequent focus value; and (iii) repeat (d) through (g).