Image Processing Device Skin Color Detection
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Solution Overview
Problem
Existing image processing methods struggle to accurately discern skin color regions due to variations in skin tone among different races or individuals, often leading to false color determination, and broadening the color range to accommodate these differences can result in non-skin colors being incorrectly identified as skin colors.
Innovation Solution
An image processing device that designates specific regions within an image, calculates hue angles and color space coordinates, and extracts similar color regions based on differences between reference and pixel values, using a combination of hue angle, color space coordinates, and chromaticness index to accurately identify skin color regions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a predetermined hue range of skin color is used for detection, then the detection method is simple, but skin color regions cannot be accurately discerned due to racial or individual differences
Solution Approach 1:
The patent changes the detection parameters from fixed predetermined hue ranges to dynamically calculated reference hue angles and reference color space coordinates based on actual image content. This allows the detection criteria to adapt to different skin tones while maintaining a systematic detection approach.
Solution Approach 2:
The patent performs preliminary calculation of reference hue angles and reference color space coordinates from a designated specific region before extracting similar color regions throughout the entire image. This preliminary action establishes accurate reference values that account for racial or individual skin color differences.
2Adaptability or versatility
If the color range is broadened to encompass skin color variations, then racial or individual differences are accommodated, but non-skin colors are wrongly determined as skin colors
Solution Approach 1:
The patent transforms the detection approach by calculating reference values (hue angles and color space coordinates) from actual image data rather than using fixed predetermined ranges. This dynamic parameter adjustment maintains adaptability to different skin tones while preventing false identification of non-skin colors.
Solution Approach 2:
The patent replaces the mechanical approach of fixed hue range comparison with a more sophisticated system that calculates reference values based on actual image content and uses multiple parameters (hue angle, color space coordinates) for more accurate discrimination.
3Measurement precision
If multiple parameters (hue angle, color space coordinates, chromaticness index) are used for detection, then detection accuracy is improved, but device complexity increases
Solution Approach 1:
The patent segments the detection process into distinct functional units: a region designating unit for selecting the specific region, a hue angle calculating unit for computing hue angles, a color space coordinates calculating unit for computing color coordinates, and a region extracting unit for final extraction. This segmentation manages complexity through modular organization.
Solution Approach 2:
The patent creates a multi-functional detection system where the same computational framework (calculating reference values and comparing parameters) can detect various similar color regions regardless of skin tone variations, making the system universally applicable to different racial or individual skin colors.
Data Source
AI summary
An image processing device extracts a similar color region from an image, based on at least a difference between a reference hue angle calculated based on a hue angle of pixels or small regions within a specific region of the image and the hue angle within the specific region, and a color difference between reference color space coordinates calculated based on color space coordinates of the pixels or small regions within the specific region and the color space coordinates within the specific region.


