Multi-frame Super-resolution Barcode Imager for Moving Logistics
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Solution Overview
Problem
In logistics operations, reading machine-readable codes on moving objects is challenging due to uncertainties in code location, speed, height variations, and limited image resolution, which is exacerbated by the need for high-resolution imaging across a wide area without increasing costs or mechanical complexity.
Innovation Solution
A multi-frame super-resolution processing system that captures multiple low-resolution images with non-integer pixel shifts and aligns them to create a high-resolution image, using interleaving techniques to enhance resolution without requiring expensive high-pixel sensors or complex mechanical movements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a sensor with many pixels (e.g., 40,000 pixels) is used to improve resolution, then image resolution is improved, but cost increases
Solution Approach 1:
The patent divides the imaging task into multiple segments by using multiple low-resolution images taken at different positions. These segmented images are then processed through super-resolution algorithms to reconstruct a high-resolution image, avoiding the need for a single expensive high-pixel sensor.
Solution Approach 2:
The patent transitions from a single-dimension approach (one high-resolution sensor) to a multi-dimensional approach by capturing images at multiple positions and combining them through computational processing. This adds the dimension of temporal and spatial sampling to achieve high resolution without requiring a high-pixel sensor.
2Measurement precision
If multiple cameras are used to cover the entire conveyor belt to improve resolution, then image resolution is improved, but cost and device complexity increase
Solution Approach 1:
Instead of using multiple cameras simultaneously, the patent uses a single camera to capture multiple sequential images of different segments of the code as the conveyor belt moves. This segmented temporal approach replaces the spatial segmentation of multiple cameras.
Solution Approach 2:
The patent introduces dynamic motion between the camera and the code on the conveyor belt. By capturing images at different positions during motion and then aligning them computationally, the system achieves high resolution without requiring multiple stationary cameras.
3Measurement precision
If tip/tilt mirrors or moving imaging devices are used to scan the region of interest to improve resolution, then image resolution is improved, but device complexity and mechanical difficulty increase
Solution Approach 1:
The patent replaces mechanical scanning systems (tip/tilt mirrors, moving imaging devices) with a computational approach. The camera remains stationary while the conveyor belt provides the relative motion, and image processing algorithms perform the alignment and super-resolution reconstruction that would otherwise require mechanical scanning.
4Measurement precision
If zoom lenses are used to increase resolution to improve measurement precision, then image resolution is improved, but device complexity increases due to moving parts
Solution Approach 1:
The patent replaces optical zoom mechanisms (which require moving lens elements) with computational zoom achieved through super-resolution processing. Multiple low-resolution images captured at different positions are processed to create a high-resolution image, eliminating the need for mechanical zoom components.
Data Source
AI summary
A system and method for reading a machine readable code associated with an object moving relative to an imaging device may include capturing a first image of the machine readable code at a first resolution. A second image of the machine-readable code with a non-integer pixel shift in alignment at the first resolution may be captured. An interleaved image may be formed from the first and second images. An image of the machine-readable code may be generated at a second resolution using the interleaved image, where the second resolution is higher than the first resolution.