Preference Color Conversion via Sub-Region Segmentation
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Solution Overview
Problem
Conventional color conversion algorithms fail to consider color distribution characteristics of different regions in an image, resulting in uniform color conversion that does not accurately represent user preferences, such as skin tones or sky colors.
Innovation Solution
An apparatus and method that divide the color space of a user's preference color into sub-regions based on color distribution characteristics, allowing for targeted color conversion of image regions using a corresponding color conversion model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If uniform color conversion is applied to all regions containing a preference color, then the conversion process is simple and fast, but the color representation accuracy deteriorates because it cannot account for different color distribution characteristics in different regions
Solution Approach 1:
The patent divides the color space into multiple sub-regions based on color distribution characteristics. Instead of applying a single uniform conversion to all regions containing a preference color, the system segments the color space and applies region-specific conversion models, thereby improving color representation accuracy while managing complexity through structured segmentation.
Solution Approach 2:
The patent implements local quality by applying different color conversion models to different sub-regions of the color space. Each sub-region has its own conversion characteristics tailored to the specific color distribution in that region, allowing for more accurate local color representation rather than using a single global conversion model.
2Measurement precision
If the color space is divided into multiple sub-regions with different conversion models, then color conversion accuracy improves, but the computational complexity and processing time increase
Solution Approach 1:
The patent performs preliminary action by pre-defining multiple sub-regions in the color space and preparing region-specific conversion models in advance. This allows the system to quickly determine which sub-region a given color falls into and apply the appropriate pre-prepared conversion model, reducing real-time computational complexity while maintaining high conversion accuracy.
Data Source
AI summary
An apparatus and method are provided for converting a preference color, in which the color space of a preference color selected by a user is divided into a plurality of sub-regions according to color distribution characteristics, and the colors of the respective regions of an input image corresponding to the user's preference color are converted into colors of proper sub-regions among the plurality of sub-regions. The apparatus for converting a preference color includes an image extraction unit which extracts at least one image region that includes a preference color from an input image, an image analysis unit which analyzes color distribution characteristics of the image region, a color-space extraction unit which extracts a divided space corresponding to the color distribution characteristics from divided spaces included in a color space of the preference color, and a color conversion unit which converts a color of the image region by using a color conversion model corresponding to the extracted divided space.