Spectacle Lens Rim Detection Using Deterministic Image Optimization
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Solution Overview
Problem
Existing methods for determining centration parameters for spectacle lenses are inefficient, error-prone, and time-consuming, hindering opticians from providing high-quality advice to customers.
Innovation Solution
A deterministic optimization method using a cost function that combines machine-learned models with digital image analysis to accurately and reliably determine the edge of spectacle lenses fitted to a frame, incorporating edge and color information, reflections, and facial features, ensuring robustness against errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual methods are used to determine centration parameters, then measurement precision can be achieved, but productivity is low and loss of time is high
Solution Approach 1:
The patent replaces manual mechanical measurement methods with an automated image processing system. The system captures images of the spectacle frame and lens, then uses computer vision algorithms to automatically determine centration parameters, eliminating the need for manual marking and measurement while maintaining high precision.
Solution Approach 2:
The system creates a digital copy (image) of the spectacle frame and lens configuration, then analyzes this digital representation to extract centration parameters. This digital copying approach allows for precise measurement without physical manipulation of the actual spectacles, improving both speed and accuracy.
2Measurement precision
If manual marking methods are used to determine optical center position, then measurement precision is achieved, but loss of time increases
Solution Approach 1:
The system performs self-service by automatically analyzing the image data and extracting centration parameters without requiring optician intervention for each measurement step. The automated algorithm processes the image, identifies the optical center, and calculates all necessary parameters independently, significantly reducing the time required compared to manual methods.
Solution Approach 2:
The image processing system operates continuously and automatically, processing images and extracting parameters without interruption or manual intervention. This continuous automated operation eliminates the discontinuous nature of manual measurement, maintaining steady progress through the entire measurement process and reducing overall time loss.
3Productivity
If automated image analysis is used to determine lens edge, then productivity increases, but measurement precision may be compromised
Solution Approach 1:
The system incorporates feedback mechanisms where the image processing algorithm continuously refines its edge detection based on the analyzed image data. By comparing detected edges against the actual lens geometry and adjusting parameters accordingly, the system maintains high precision while achieving automated high-speed processing.
Solution Approach 2:
The system dynamically adjusts processing parameters based on the specific characteristics of the captured image and lens configuration. By adapting edge detection parameters to match the actual optical geometry, the system ensures high measurement precision is maintained even during automated high-speed operation.
Data Source
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AI summary
The invention relates to a computer-implemented method for determining the representation of the edge (26) of a spectacle lens (28) or of a left spectacle lens (28) and of a right spectacle lens (29) for a spectacle frame (20). According to the invention, the following steps are carried out: providing image data b(x) for the spectacle frame (20) with a worn frame front (24); calculating information data I(x) derived from the image data b(x); calculating a deterministically optimisable cost function E(u) which links the information data I(x) to spectacle lens data u(x), the spectacle lens data u(x) describing the spatial extent of at least one spectacle lens (28) held in the frame front (24); and defining a contour of an edge (26) of the spectacle lens (28) or of the left spectacle lens (28) and of the right spectacle lens (29) by optimising the cost function E(u).