Effect Image Generation Using Edge-Based Graphic Patch Fusion
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Solution Overview
Problem
Existing image processing applications do not generate effect images rich enough in content.
Innovation Solution
An effect image generation method involving creating initial graphic patches, performing edge detection, screening these patches based on the edge detection result, drawing set materials in the target patches, and fusing the initial effect image with the original image to enhance the image content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If traditional image processing methods are used, then the processing speed is fast, but the content richness of the generated effect image is insufficient
Solution Approach 1:
The image processing is divided into multiple stages: edge detection to identify target regions, graphic patch generation to create effect elements, and composite image generation to combine them. This segmentation allows complex content-rich effects to be achieved through modular processing steps.
Solution Approach 2:
Graphic patches are pre-generated and stored in a library before the actual image processing. These pre-prepared effect elements (snowflakes, stars, hearts, etc.) are then selectively applied to detected edges, avoiding the need to generate effects in real-time and reducing processing complexity.
2Adaptability or versatility
If simple effect generation is used, then the processing complexity is low, but the display effect and diversity of the image is poor
Solution Approach 1:
Different graphic patches with distinct visual characteristics are applied to different edge regions of the image. The system selects and applies appropriate effect elements based on the local characteristics of each edge, creating diverse and adaptive visual effects throughout the image rather than applying a uniform effect.
Solution Approach 2:
Multiple types of graphic patches (different shapes, sizes, and visual styles) are combined in a single image processing operation. The composite image generation module integrates various effect elements with the original image, creating rich and diverse visual outcomes through composition of multiple graphical components.
3Measurement precision
If precise edge detection and patch screening are performed, then the accuracy of effect placement is improved, but the processing time increases
Solution Approach 1:
Instead of performing complex real-time analysis for each edge detection and patch matching operation, the system uses pre-detected edge information and pre-generated graphic patches. The screening process compares edge characteristics with stored patch templates, significantly reducing computation time while maintaining accurate placement.
Solution Approach 2:
The system adjusts detection parameters and screening criteria to optimize the balance between accuracy and speed. By tuning the sensitivity of edge detection and the matching thresholds for graphic patches, the system achieves satisfactory precision without excessive processing time.
Data Source
AI summary
An effect image generation method and apparatus, a device, and a storage medium. The effect image generation method includes: creating a plurality of initial graphic patches; performing edge detection on an original image to obtain an edge detection result; screening the plurality of initial graphic patches based on the edge detection result to obtain a target graphic patch; drawing set materials in the target graphic patch to obtain an initial effect image; and fusing the initial effect image with the original image to obtain a target effect image.