Parametric Frame Rim Model for Spectacle Centering
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Solution Overview
Problem
Current methods for determining centering parameters for spectacle frames require separate tracer data sets for each frame, which are time-consuming to generate and laborious, leading to increased waiting times for customers and inefficiencies in the optician's workflow, especially since they often rely on three-dimensional data sets that not all tracers can provide.
Innovation Solution
A parametric frame rim model is created using a multiplicity of data sets describing the course of spectacle frames, allowing for a versatile model that can fit various frames without the need for separate tracer data sets, utilizing techniques like principal component analysis and probability distributions to account for diverse frame shapes and noisy data, and can be based on either 2D or 3D data sets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If separate tracer data sets are generated for each spectacle frame, then accurate frame rim identification is achieved, but the process becomes time-consuming and laborious
Solution Approach 1:
The patent creates a universal parametric frame rim model that can represent multiple spectacle frame types through a single mathematical framework. The model uses adjustable parameters (radius, curvature, segment angles) to adapt to different frame geometries, eliminating the need for separate tracer data sets for each frame while maintaining identification accuracy.
Solution Approach 2:
The invention transforms fixed tracer data sets into a flexible parametric model where frame geometry is controlled by variable parameters. By changing these parameters (such as arc radius, curvature values, and segment configurations), the same model can accurately represent diverse frame shapes, reducing data generation time while preserving measurement precision.
2Reliability
If three-dimensional data sets are used for frame rim modeling, then comprehensive frame information is obtained, but not all tracers can provide such data
Solution Approach 1:
The patent employs 3D coordinate systems and spatial mathematics to create a parametric model that can represent frame geometry in three dimensions. However, the model can accommodate 2D tracer data by interpreting it within the 3D framework, thus maintaining tracer compatibility while achieving comprehensive frame information through mathematical dimensionality rather than requiring 3D tracer capabilities.
3Adaptability or versatility
If a parametric frame rim model is created to fit various frames, then versatility is improved, but handling diverse frame shapes and noisy data becomes complex
Solution Approach 1:
The patent divides the frame rim into multiple geometric segments (typically four arcs) that can be independently parameterized. Each segment is defined by its own radius, curvature, and angular position, allowing the model to adapt to diverse frame shapes through localized parameter adjustments rather than requiring complex global modifications, thus managing versatility without excessive complexity.
4Measurement precision
If manual centering parameter determination is performed by opticians, then accurate optical center alignment is achieved, but the process is labor-intensive and subject to visual judgment variability
Solution Approach 1:
The patent replaces the manual visual judgment process with an automated computer-based system. The parametric frame rim model enables algorithmic identification of frame geometry and automatic calculation of centering parameters, substituting the optician's visual measurement and manual determination with computational methods that maintain accuracy while significantly improving efficiency and reducing subjectivity.
Data Source
AI summary
A method for providing a mounting edge model, a corresponding computer program, and a corresponding computing device are disclosed. To provide the mounting edge model, first a plurality of data sets is provided, each of which describes a course of a mounting edge. Such data sets can be obtained from tracer data, for example. On the basis of the data sets, a parametric mounting edge model is then derived.