Image Processing Device Selective Super-Resolution
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Solution Overview
Problem
In production facilities, the use of fixed focal length lens units in imaging devices can result in insufficient resolution when imaging small target objects, leading to extended processing times due to the necessity of multi-frame super-resolution processing, which increases the load and cycle time of image processing.
Innovation Solution
The image processing device selectively executes super-resolution processing based on the type of target object, switching between low and high resolution data to suppress excessive processing, thereby reducing the load and time required for image processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If super-resolution processing is executed for all target objects, then measurement precision is improved, but processing time increases
Solution Approach 1:
The system dynamically changes the processing parameter (resolution level) based on the size parameter of the target object. Small target objects trigger super-resolution processing to achieve sufficient measurement precision, while large target objects use standard resolution processing to minimize processing time. This parameter adaptation resolves the contradiction by matching processing intensity to actual needs.
2Manufacturing precision
If super-resolution processing is executed for all image data, then manufacturing precision is improved, but productivity decreases
Solution Approach 1:
The system applies different processing qualities to different portions of the workload based on target object characteristics. Instead of uniformly applying super-resolution processing to all images, it selectively applies high-quality processing only to images containing small target objects that require enhanced resolution for accurate recognition. This local quality approach maintains high manufacturing precision where needed while preserving overall productivity.
3Measurement precision
If a narrow camera visual field is used, then measurement precision is improved, but adaptability decreases
Solution Approach 1:
The system dynamically adjusts the effective visual field coverage by selectively processing different regions or objects at different resolution levels. When small target objects are detected, the system applies super-resolution processing to enhance detail in those specific regions. This dynamic approach allows the system to maintain narrow visual field settings (which provide high resolution) while adapting to handle various target object sizes through intelligent processing selection.
Data Source
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AI summary
An object is to provide an image processing device capable of reducing the load of image processing while shortening the time required for the image processing which uses super-resolution processing. The image processing device is provided with a process determination section which determines an execution necessity of the super-resolution processing in relation to image data during execution of a production process for every type of target object, a super-resolution processing section which executes the super-resolution processing which uses a plurality of items of the image data according to determination results of the process determination section to generate high resolution data, and a state recognition section which recognizes a state of the target object based on, of the image data and the high resolution data, the one corresponding to the determination results of the process determination section.