Radial Pattern Decoding via Grid Reconstruction for Editable Visuals
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Solution Overview
Problem
Conventional techniques for creating and implementing visual patterns are limited to specific scenarios and do not support subsequent editing, resizing, or flexible arrangement of visual patterns.
Innovation Solution
A digital image radial pattern decoding system that unfolds, inflates, and smoothes radial patterns to generate a grid pattern, allowing for the conversion of radial pattern cells into radial vector patterns, enabling editing and flexible implementation of visual patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional techniques are used to create visual patterns, then the patterns can be created for dedicated scenarios, but subsequent editing, arrangement, styling, and use are limited
Solution Approach 1:
The system segments the visual pattern into discrete pattern cells that can be independently manipulated. Each pattern cell is identified and extracted from the input image, allowing individual editing, arrangement, and styling operations without affecting the entire pattern structure.
Solution Approach 2:
The system transforms the visual pattern from a fixed 2D image into a structured representation with additional dimensional information. Pattern cells are organized in a grid structure with metadata about their positions, transformations, and styling properties, enabling flexible manipulation in multiple dimensions.
2Adaptability or versatility
If conventional techniques are used to create visual patterns, then the patterns can be implemented in specific scenarios, but resizing and flexible arrangement are not supported
Solution Approach 1:
The system creates a dynamic pattern representation where pattern cells can be resized, repositioned, and reconfigured while maintaining visual quality. The structured data model allows real-time adjustments to pattern dimensions and arrangement without regenerating the entire pattern from scratch.
Solution Approach 2:
The system enables modification of pattern parameters such as cell size, spacing, orientation, and styling properties. By changing these parameters in the structured representation, the pattern can be resized and rearranged while maintaining manufacturing precision through controlled parameter adjustments.
3Measurement precision
If radial pattern decoding is performed with high quality and numerical stability, then computing device operation and accuracy are enhanced, but processing complexity increases
Solution Approach 1:
The system replaces complex radial pattern decoding mechanics with a simplified grid-based approach. By transforming the radial pattern into a structured grid representation, the system achieves high decoding accuracy through straightforward geometric transformations rather than complex iterative algorithms.
Solution Approach 2:
The system introduces an intermediate structured representation layer between the input image and the final pattern output. This intermediate grid structure with pattern cell metadata serves as a mediator that simplifies processing while maintaining numerical stability and decoding accuracy throughout the transformation pipeline.
Data Source
AI summary
A digital image radial pattern decoding system is described. In one example, an unfolded digital image is formed by the radial pattern decoding system by unfolding a radial pattern in a digital image. An inflated digital image is then generated by the radial pattern decoding system by upsampling the unfolded radial pattern. A grid pattern is determined by the radial pattern decoding system based on the inflated digital image. A radial pattern cell is then generated based on a reverse transform of the grid pattern. A visual pattern is generated by the radial pattern decoding system based on the radial pattern cell.