Skin Color Conversion Apparatus Using Race-Specific Chromaticity Adjustment
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Solution Overview
Problem
Current display devices and image forming technologies fail to accurately reproduce skin colors across different races, leading to user confusion when multiple races are depicted together in an image, as they output colors without adjustment for individual skin tones.
Innovation Solution
A color conversion method and apparatus that determine the race of a skin region in an image by analyzing pixel characteristics and preferred skin color information, selecting the most appropriate skin color from preset data for each race, and adjusting the image colors using nonlinear weights to enhance visual satisfaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If color reproduction is performed without race-specific adjustment, then device complexity is reduced, but color accuracy for skin tones across different races deteriorates
Solution Approach 1:
The system pre-stores multiple preferred skin color information sets corresponding to different races in a storage unit before actual image processing. This preliminary preparation allows the system to quickly retrieve and apply appropriate color corrections without complex real-time calculations, thereby improving skin color accuracy while maintaining relatively simple device complexity.
Solution Approach 2:
The system changes color parameters (chromaticity coordinates Cb and Cr) based on detected race characteristics. By adjusting these specific color parameters according to race-specific preferred skin color information, the system achieves accurate skin tone reproduction across different races without requiring complete redesign of the color processing system.
2Adaptability or versatility
If multiple preferred skin color information per race is stored, then adaptability to different skin tones within races is improved, but loss of information increases due to larger data storage requirements
Solution Approach 1:
The system stores multiple preferred skin color information sets specifically for dark-skin toned races, while storing fewer sets for light-skin toned races. This local differentiation optimizes storage efficiency by allocating more color variations to races with greater skin tone diversity, thereby improving adaptability where needed while minimizing unnecessary data storage for races with narrower skin tone ranges.
3Measurement precision
If race determination is performed using Euclidean distance calculation, then measurement precision of race classification is improved, but device complexity increases due to additional computational requirements
Solution Approach 1:
The system replaces complex machine learning or neural network-based race detection algorithms with a simpler Euclidean distance calculation method in chromaticity space. This substitution maintains sufficient race detection accuracy while significantly reducing computational complexity and processing requirements, making the system more practical for real-world deployment.
Data Source
AI summary
A color conversion method includes determining a race by recognizing a skin region in an input image, selecting a preferred skin color to apply to the skin region based on a plurality of preferred skin color information preset per race, and correcting a color of the skin region using the selected preferred skin color. Additionally, a color conversation apparatus includes a control unit to determine a race by recognizing a skin region in an input image input, and to select a preferred skin color to apply to the skin region, based on the plurality of the preferred skin color information stored in a storage unit, and a compensation unit to correct a color of the skin region using the preferred skin color selected by the control unit. Hence, the skin color per race can be adequately converted to the color which can satisfy the user.