Skin Diagnostic Image Processing for Accurate Visual Estimation
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Solution Overview
Problem
Existing skincare and cosmetic visualization methods lack accuracy and consistency, leading to disillusioned consumers due to speculative data-based predictions, which affects purchasing decisions.
Innovation Solution
A skin diagnostic technique combined with image processing methods that capture user skin images, process them against a database using specified parameters to apply image filters, generating simulated skin images for accurate visual estimations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If speculative data-based predictions are used for skincare visualization, then the visualization process is simple and quick, but the accuracy and consistency of results deteriorate
Solution Approach 1:
The system performs preliminary diagnostic operations on user skin images before generating visualizations. Skin diagnostic data is collected and processed in advance to create an accurate baseline representation of the user's skin conditions, which then informs the consumer results visualization process
Solution Approach 2:
The patent introduces an intermediary processing layer between raw skin images and consumer results visualizations. Image processing filters are applied to skin images to generate processed skin image data that accurately represents actual skin conditions, serving as a reliable intermediary foundation for predicting consumer results
2Reliability
If detailed skin diagnostic operations are performed, then the accuracy of visual estimations is improved, but the processing time and system complexity increase
Solution Approach 1:
The system applies image processing filters selectively to specific portions of skin images rather than processing entire images uniformly. This partial action approach focuses computational resources on diagnostically relevant areas, maintaining accuracy while reducing overall processing time
Solution Approach 2:
The skin diagnostic process is segmented into distinct operational stages: initial skin image capture, diagnostic operation application, image processing filter application, and consumer results generation. This segmentation allows each stage to be optimized independently, improving overall efficiency while maintaining reliability
Data Source
AI summary
Skin diagnostic techniques employed in conjunction with image processing techniques. For example, a user information module captures a user skin image. A graphical user interface enables selection of a skin-related application from a plurality of skin-related applications. A processor determines user skin image data from the user skin image, and identifies one or more sets of skin image data in the skin image database that correspond to the user skin image data based on one or more parameters specified by the skin-related application. The processor applies at least one image processing filter that corresponds to the one or more identified sets of skin image data from the skin image database to the user skin image to generate a simulated user skin image. An output display displays the simulated user skin image.