Automated Program Generation for Image Transformation
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Solution Overview
Problem
Existing visual programming methods, such as Scratch, require users to manually select and combine commands to change images, which can be cumbersome and error-prone, especially when trying to find suitable programs for similar images.
Innovation Solution
A program generating method that acquires an image set, accesses a database of image sets and associated computer programs, calculates integrated similarities based on image similarities and completeness, and retrieves similar images to automatically generate a computer program for image transformation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If users manually select and combine visual blocks to generate programs, then program customization and adaptability are improved, but operation complexity and time consumption increase
Solution Approach 1:
The system automatically generates programs by analyzing the target image and selecting appropriate visual blocks without requiring manual user configuration. The program generating device performs image analysis, retrieves suitable programs from storage, and automatically applies them to transform the target image, enabling the system to serve itself rather than requiring continuous user intervention.
Solution Approach 2:
The system pre-stores multiple programs with associated visual blocks in a storage device before runtime. These programs are organized and ready for retrieval based on image characteristics, allowing the system to quickly select and apply appropriate programs without requiring users to manually assemble blocks during operation.
2Manufacturing precision
If users manually configure visual blocks for image transformation, then program suitability for specific images is improved, but time consumption and operational effort increase
Solution Approach 1:
The system performs image analysis on the target image to extract features and characteristics, then uses this feedback information to automatically select the most suitable pre-stored programs. The analysis results guide the program selection process, ensuring that the chosen programs are well-matched to the specific image being transformed without requiring manual user judgment.
Solution Approach 2:
The system replaces the manual mechanical process of users selecting and configuring visual blocks with an automated computational process. The program generating device uses image analysis algorithms and automated program selection logic to substitute for human manual operations, significantly reducing time consumption while maintaining program suitability.
3Measurement precision
If comprehensive image analysis is performed to select suitable programs, then program selection accuracy is improved, but computational complexity increases
Solution Approach 1:
The image analysis process is divided into multiple segments or stages, where different aspects of the image (such as color, shape, texture, content) are analyzed separately. Each segment focuses on specific features, making the overall analysis more manageable and less computationally intensive while maintaining comprehensive coverage for accurate program selection.
Data Source
AI summary
A program generating method acquires a first image set, and retrieves a similar image that is similar to a processing target image included in the first image set, from a database. For each of N number of second image sets in the database, an integrated similarity of an image included in the second image set with respect to the processing target image is calculated based on a first similarity between the image included in the second image set and the processing target image, a second similarity between the second image set and the first image set, and the completeness of the first image set, and the similar image is retrieved based on the integrated similarity.