Signal Processing Block Conversion via Image Recognition
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Solution Overview
Problem
Existing engineering tools for configuring automation systems face significant challenges when converting signal processing functionalities from one development status to another, as this process is time-consuming and costly, requiring manual effort and knowledge of the graphic representation to implement and reconfigure the application program.
Innovation Solution
A method is introduced that uses image recognition to scan and compare graphic representations of signal processing functionalities based on different formats, generating intermediate codes and replacing function modules to automatically convert the representation from one format to another, enabling the generation of an executable application program for configuration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual conversion of graphical representation between different formats is performed, then conversion accuracy can be maintained, but time consumption and cost increase significantly
Solution Approach 1:
The patent replaces the manual mechanical conversion process with an automated image recognition system. The configuration program captures screenshots of the graphical representation, processes images to identify function blocks and connections, and automatically generates the target format configuration, eliminating manual intervention while maintaining accuracy through systematic image analysis.
Solution Approach 2:
The patent introduces an intermediate image processing stage between the source graphical representation and the target configuration. Screenshots are captured and processed through image recognition algorithms that extract function block types, parameters, and connection relationships, serving as a mediator that enables accurate automated conversion without direct manual mapping.
2Manufacturing precision
If manual conversion of graphical representation between different formats is performed, then conversion quality can be ensured, but cost increases significantly
Solution Approach 1:
The patent replaces expensive manual expert conversion with an automated configuration program that performs image capture, processing, and configuration generation. This substitution eliminates the need for specialized human expertise while maintaining conversion quality through systematic algorithms that consistently identify and map function blocks and connections.
Solution Approach 2:
The configuration program performs self-service by automatically capturing its own graphical representation screenshots, processing these images to extract configuration data, and generating the target format configuration without external intervention. This self-contained process reduces costs by eliminating manual labor while maintaining quality through automated quality control.
3Productivity
If automated image recognition is used for format conversion, then time consumption is reduced, but conversion accuracy may be compromised
Solution Approach 1:
The patent uses screenshots as an intermediary that preserves the exact visual representation of the source configuration. The image recognition process analyzes these high-fidelity screenshots to identify function blocks, their parameters, and connection relationships, ensuring accurate extraction of configuration data while enabling rapid automated processing.
Solution Approach 2:
The configuration program provides feedback by displaying the generated configuration and allowing verification against the original graphical representation. This feedback mechanism enables validation of conversion accuracy while maintaining high productivity through automated processing, as errors can be identified and corrected systematically.
Data Source
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AI summary
The invention relates to generating a graphical representation of a signal processing functionality with function blocks based on a first format, each with at least one signal input and signal output for specifying respective signal processing sub-functionalities, and with function blocks based on a second format, each with at least one signal input and signal output for specifying respective signal processing sub-functionalities. An image of a graphical representation of the signal processing functionality with function blocks based on the second format is provided and scanned along a first and second scanning direction. For each image, image recognition is performed, a first and second data set are generated, and a first and second intermediate code are generated, which are then compared.If the comparison results in an identity between the first and second intermediate codes, at least one function block based on the first format is selected for at least one known signal processing sub-functionality used in the generation, and the signal processing functionality is graphically represented, whereby recognized function blocks are replaced by selected function blocks based on the first format.