Dual-Resolution Imaging Engine Normalization
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Solution Overview
Problem
Industrial scanners with multiple camera systems of different resolutions face challenges in efficiently processing and decoding images at a host processor, as the processor must dynamically handle images of varying sizes and resolutions without prior knowledge, leading to lost frames and longer decode times.
Innovation Solution
A method involving an image normalization process, where captured image data from near and far field sensors is normalized to a consistent size or frame rate by techniques such as padding, cropping, binning, or scaling, before being communicated to a host processor for efficient processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the host processor dynamically receives and processes images of different sizes and resolutions from multiple cameras, then the system can capture a wide range of distances, but the processing time increases and frames are lost
Solution Approach 1:
The patent applies preliminary action by performing image normalization at the camera level before images are sent to the host processor. Each camera pre-processes its images to a standard resolution, so the host processor receives uniform images ready for immediate decoding, eliminating dynamic reprogramming needs and reducing processing delays
Solution Approach 2:
The patent introduces an intermediary normalization layer between the multiple cameras and the host processor. This intermediary component standardizes images from different resolution cameras, allowing the host processor to handle diverse scanning ranges while maintaining consistent processing performance
2Adaptability or versatility
If the host processor is re-programmed for different image sizes, then it can handle various camera resolutions, but decode times increase and frames are lost
Solution Approach 1:
The normalization process is performed in advance at the camera level, converting all images to a standard resolution before transmission. This preliminary standardization eliminates the need for the host processor to dynamically re-program itself for different image sizes, maintaining consistent decode times across all scanning ranges
Solution Approach 2:
The patent changes the resolution parameter at the source by normalizing all camera outputs to a fixed size. This parameter standardization transforms the variable-resolution input into a constant-resolution stream, allowing the host processor to operate with fixed, optimized decoding parameters regardless of the original camera resolution
Data Source
AI summary
Devices having a long-range imaging engine formed of two cameras having different resolution are disclosed herein. An example imaging engine includes a front-end, with the cameras, terminated in a communication interface for coupling to an external host processor that performs image processor. The front-end has a near field image sensor and a far field image sensor, and a normalization processor to receive the respective image data from the sensors and normalize that image data prior to sending to the host processor. Normalization includes adjusting an image size, aspect ratio, or pixel count complying with data rate constraints imposed by the communication interface or the host processor.