Curved Visual Mark Decoding via 3D Mesh Projection
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Solution Overview
Problem
Existing technologies face difficulties in accurately reading visual codes, such as QR codes, on curved or deformed surfaces due to the complexity of identifying and processing these codes.
Innovation Solution
The implementation of an apparatus and method that uses a processor to create a 2D reference mesh and determine a 3D mesh with a minimal reprojection error, allowing for the accurate reading of visual codes on variously shaped objects by sampling components and analyzing the image to decode the information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If visual codes are placed on curved or deformed surfaces, then the applicability and versatility of visual codes is improved, but the difficulty of detecting and measuring the visual code increases
Solution Approach 1:
The patent transforms the curved visual code problem from a 2D image processing task into a 3D geometric problem. By creating a 3D mesh model of the surface and mapping the visual code onto it, the system can account for curvature and deformation in three-dimensional space, then project the corrected code back to 2D for decoding.
Solution Approach 2:
The patent introduces a 3D mesh model as an intermediary between the curved surface and the visual code. This mesh serves as a intermediate representation that captures the surface geometry, allowing the system to compute reprojection errors and iteratively optimize the mapping between the visual code and the curved surface.
2Measurement precision
If complex processing methods are used to read curved visual codes, then the measurement precision is improved, but the processing resource consumption increases
Solution Approach 1:
The patent performs preliminary actions by pre-computing the 3D mesh model of the surface and pre-establishing the correspondence between mesh vertices and image pixels. This preliminary geometric modeling allows the subsequent code reading process to focus only on optimizing the projection parameters rather than computing the entire geometric transformation from scratch.
Solution Approach 2:
The patent replaces complex iterative image processing methods with a geometric projection model. Instead of using computationally intensive image warping or deformation correction algorithms, the system uses analytical geometry to compute the optimal projection of the visual code onto the curved surface, significantly reducing computational burden.
3Device complexity
If traditional image processing methods are used for curved visual codes, then the device complexity is reduced, but the reliability of reading the code decreases
Solution Approach 1:
The patent changes the parameter space from direct image pixel coordinates to 3D mesh vertex coordinates and projection parameters. By optimizing the projection parameters (such as camera position, orientation, and focal length) rather than directly manipulating image pixels, the system achieves more reliable code reading while maintaining relatively simple processing logic.
Data Source
AI summary
According to examples, an apparatus may include a processor and a non-transitory computer readable medium on which is stored instructions that may cause the processor to create a 2D reference mesh for an image of a curved visual mark, establish correspondences between finder pattern points in the curved visual mark and points of the 2D reference mesh, and determine a curved 3D mesh having a radius that results in a minimal reprojection error of a projective transform estimated for correspondences between the 2D reference mesh and the curved 3D mesh while the radius remains below a predefined upper limit. The instructions may also cause the processor to sample components of the curved visual mark in elements of the determined curved 3D mesh to form a 2D planar image of the curved visual mark and analyze the 2D planar image of the curved visual mark to read the curved visual mark.