Picture-in-Picture Multi-Sensor Imaging for Faster Optical Code Decoding
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Solution Overview
Problem
Conventional multi-sensor systems face challenges in efficiently processing images from sensors with different configurations, resolutions, and technologies, requiring computationally intensive algorithms and additional processing capabilities.
Innovation Solution
A multi-sensor system generates a picture-in-picture image by combining image data from sensors with different configurations, resolutions, and technologies, allowing simultaneous processing and decoding of optical codes without prior knowledge of the capturing sensor, using techniques like binning, windowing, and superimposing images to achieve uniform size and resolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple image sensors with different configurations, resolutions, and technologies are used to capture images from different fields (near-field and far-field), then the system can obtain images with extended depth-of-field and decoding range, but the image processing becomes computationally intensive and complex
Solution Approach 1:
The patent divides the image processing task into segments: first identifying which sensor captured the target image, then routing that specific image to the decoding unit for processing. This segmentation avoids the need to process all images from all sensors, significantly reducing computational complexity while maintaining the ability to handle multiple sensor types and configurations.
Solution Approach 2:
The patent introduces an intermediary component (the processor or control unit) that acts as a mediator between the multiple image sensors and the decoding unit. This intermediary identifies the capturing sensor and determines which image to process, simplifying the overall system architecture and reducing the computational burden on the decoding unit.
2Measurement precision
If images from multiple sensors with different resolutions and formats are processed separately to analyze image data, then comprehensive image analysis is achieved, but processing time and computational resources increase
Solution Approach 1:
The patent extracts only the necessary image data from the multiple sensors for processing. By identifying which sensor captured the target and selecting only that specific image for decoding, the system avoids processing unnecessary images from other sensors, thereby reducing processing time while maintaining analysis accuracy.
Solution Approach 2:
The patent performs preliminary action by identifying the capturing sensor and selecting the appropriate image before the actual decoding process. This pre-processing step ensures that only relevant images are processed, optimizing both accuracy and processing efficiency.
3Adaptability or versatility
If image sensors with different configurations and output formats are integrated to handle various target distances, then the system can decode optical codes at extended ranges, but additional processing capabilities are required to analyze images in various formats
Solution Approach 1:
The patent implements a universal processing approach where the processor or control unit handles multiple sensor types and configurations through a single unified workflow. The system universally identifies the capturing sensor and routes the appropriate image to the decoding unit, eliminating the need for multiple specialized processing paths and reducing overall system complexity.
Data Source
AI summary
The disclosure relates to systems and methods for combining images captured by at least two image sensors of a multi-sensor image system into a single image frame for analysis, where the combined image frame includes the image data captured by each sensor. The captured images may include image data for an optical code on an item being processed. The multi-sensor system includes a decoding unit operable to analyze the combined image frame and decode the optical codes from one or both images contained within the combined image frame.