Image Deformation via Fragment Ratio Control
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Solution Overview
Problem
Existing image deformation methods require manual user intervention and are not highly precise, limiting flexibility and efficiency in transforming original images into desired shapes.
Innovation Solution
An image deformation method and device that automatically deform an original image into a target shape by fragmenting the image, deforming image fragments based on a ratio of deformation at the center to deformation at the edge, and stitching them back together, allowing users to input the target shape for precise control without manual operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual user intervention is used for image deformation, then flexibility in controlling the deformation process is improved, but operation complexity and time consumption increase
Solution Approach 1:
The image is divided into multiple fragments or regions, each of which can be deformed independently according to the target shape requirements. This segmentation allows automated processing of different image regions while maintaining overall control, reducing manual intervention complexity.
Solution Approach 2:
The patent employs parameter-based deformation control where deformation ratios, transformation matrices, and geometric parameters are automatically calculated and adjusted. This allows flexible deformation control through parameter optimization rather than manual point-by-point adjustment, reducing operational complexity while maintaining adaptability.
2Productivity
If automated image deformation is implemented, then productivity and precision are improved, but control flexibility may be reduced
Solution Approach 1:
The system incorporates feedback mechanisms where deformation results are evaluated against target shape requirements, and transformation parameters are iteratively optimized. This automated feedback loop maintains high productivity while adapting to different target shapes and image characteristics without manual intervention.
Solution Approach 2:
The deformation process uses dynamic parameter adjustment where transformation ratios and geometric parameters are automatically optimized based on real-time processing feedback. This allows the automated system to adapt flexibly to different deformation requirements while maintaining high processing speed and precision.
3Device complexity
If uniform deformation ratio is applied throughout the image, then processing simplicity is improved, but deformation precision at different regions deteriorates
Solution Approach 1:
The patent applies different deformation ratios and transformation parameters to different regions of the image based on their specific requirements. Edge regions may receive different deformation treatment compared to central regions, allowing high precision deformation while managing processing complexity through systematic regional classification.
Data Source
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AI summary
Disclosed in embodiments of the present invention are an image deformation processing method, device and storage medium. The method comprises: obtaining an original image, obtaining a target shape; according to the deformation ratio of the center and edge of the original image, deforming the original image into a target image; the edge of the target image further away from the center of the target image, larger the deformation is, the shape of the target image is the target shape; and displaying the target shape.