RBX Color-Space Transformation for Skin Condition Severity Assessment
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Solution Overview
Problem
Current methods for skin examination using RBX color-space transformation lack clinical applicability and effectiveness in accurately determining the severity of skin conditions such as rosacea and monitoring therapy effects.
Innovation Solution
A method involving RBX color-space transformation to decompose skin images into Red and Brown components, calculating average intensity values, and comparing R-G values to assess skin conditions, with the use of human machine interface devices like desktop computers or mobile phones for image capture and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If RBX color-space transformation is used to decompose skin images into Red and Brown components, then the ability to analyze hemoglobin and melanin distribution is improved, but the clinical applicability and accuracy in determining skin condition severity remain insufficient
Solution Approach 1:
The patent transforms the skin image from RGB color space to RBX color space, changing the parameter representation of skin colors. This transformation separates hemoglobin (Red component) and melanin (Brown component) distributions, enabling quantitative analysis of skin conditions through calculated parameters like average intensity values and R-G differences, thereby improving measurement precision without requiring complex additional hardware
Solution Approach 2:
The patent replaces complex clinical assessment mechanisms with an automated image processing system. By using computational algorithms to calculate R-G values and compare them against reference values, the system substitutes manual clinical judgment with objective, standardized automated analysis, improving accuracy while maintaining manageable system complexity
2Reliability
If average intensity values are calculated from RBX component images to assess skin conditions, then the objectivity of skin condition assessment is improved, but the ability to monitor therapy effects over time remains insufficient
Solution Approach 1:
The patent establishes a feedback mechanism by comparing the calculated R-G value of the suspected subject against a reference R-G value from a healthy subject or baseline measurement. This feedback loop enables objective assessment of skin condition severity and allows monitoring of changes over time during therapy, thereby enhancing both reliability and adaptability for treatment evaluation
Solution Approach 2:
The patent performs preliminary decomposition of skin images into RBX components and calculates reference R-G values from healthy subjects or baseline measurements before therapy begins. This preliminary action establishes an objective baseline for comparison, enabling both reliable initial assessment and subsequent monitoring of therapy effects through longitudinal comparison
3Manufacturing precision
If R-G values are calculated and compared to reference values to determine skin condition, then the standardized assessment capability is improved, but the clinical applicability across different skin diseases and treatment types remains insufficient
Solution Approach 1:
The patent creates a universal assessment system based on RBX color-space transformation and R-G value calculation that can be applied across multiple skin conditions (rosacea, psoriasis, atopic dermatitis, etc.) and various treatment modalities (laser therapy, topical medications, chemical peels). The standardized methodology provides a multi-functional tool that maintains consistency while adapting to different clinical scenarios through comparative analysis against appropriate reference values
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables accurate determination of skin condition severity and monitoring of therapy effects by providing a standardized reference for R-G values, facilitating better clinical assessment and treatment evaluation.
Implementation Method 1
decomposing the skin image into an RBX image through RBX color-space transformation; decomposing the skin image into a Red component image through RBX color-space transformation
Implementation Method 2
Polarized light is preferably adopted for taking the images because the cross-polarized image can eliminate the specular reflection of the skin, present the color below the stratum corneum
Data Source
AI summary
The present invention discloses a method for detecting skin conditions, and the method includes the steps of: capturing a skin image from a suspected subject; decomposing the skin image into an RBX image through RBX color-space transformation; and determining skin condition of the subject according to a parameter of a color model of the RBX image.