Geometry Matching for Precise Curve Alignment in Digital Tracing
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Solution Overview
Problem
Existing systems for generating and tracing curves in graphic design are inaccurate and inefficient, particularly when dealing with precise geometric shapes, leading to excessive memory usage and device interactions due to imperfect tracing and overedited curves.
Innovation Solution
A geometry matching system that utilizes a geometry matching algorithm to detect corners in digital images, sample curves between corners, and perform similarity comparisons to generate precise geometric shapes, reducing the need for editing and refining traced curves.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing curve tracing systems are used, then basic curve generation is possible, but accuracy in generating precise geometric shapes deteriorates
Solution Approach 1:
The system performs preliminary corner detection and curve sampling before final geometry matching. By pre-identifying corner points and sampling curve characteristics, the system prepares structured data that enables more accurate geometric shape reconstruction, resolving the contradiction between basic tracing capability and geometric precision
Solution Approach 2:
The patent replaces traditional mechanical curve tracing methods with a computational geometry matching algorithm. Instead of relying on manual or simple automated tracing mechanisms, the system uses corner detection, curve sampling, and mathematical geometry comparison to achieve precise geometric shape generation, thereby improving both tracing accuracy and geometric reliability
2Productivity
If traditional curve generation methods are used, then simple designs can be created, but efficiency deteriorates due to excessive editing
Solution Approach 1:
The geometry matching algorithm performs self-correction by automatically comparing sampled curves with candidate geometries and adjusting the output to match precise geometric shapes. This self-service capability eliminates the need for manual editing and refinement, thereby improving design efficiency while reducing time loss
Solution Approach 2:
The system implements feedback through the geometry matching process, where the sampled curve characteristics are continuously compared against candidate geometric shapes. This feedback mechanism allows the system to automatically adjust and refine the generated curves, reducing the need for subsequent manual editing and improving overall productivity
3Quantity of substance
If imperfect tracing is used, then curve generation is possible, but memory usage deteriorates due to overedited curves
Solution Approach 1:
The system extracts only the essential geometric characteristics from the input image by detecting corners and sampling key curve points. By extracting this minimal necessary data rather than processing entire curves, the system maintains high tracing quality while significantly reducing memory usage and storage requirements
Data Source
AI summary
The present disclosure relates to systems, non-transitory computer-readable media, and methods for aligning curves to precise geometric shapes using a geometry matching algorithm. For example, the disclosed systems generate a set of discrete points along a curve depicted in a digital image by sampling the curve spanning between a first corner and a second corner depicted in the digital image. The disclosed systems determine an order for comparing the set of discrete points with a first geometry and a second geometry by comparing a centroid of the curve with a centroid of the first geometry and a centroid of the second geometry. The disclosed systems also determine, according to the order, a first similarity of the curve to the first geometry and a second similarity of the curve to the second geometry. The disclosed systems generate curve segments that align with one of the first geometry or the second geometry.