AI Skin Tone Correction for Individual Users in Digital Images
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Solution Overview
Problem
Existing image editing technologies fail to accurately detect and apply skin tone correction to individual user images within a single digital image.
Innovation Solution
The system uses AI functionality to detect and apply skin tone correction to individual user images within a single user image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional color correction is applied to the entire digital image based on the most prominent skin tone, then the processing is simple and fast, but the skin tone of individual users cannot be accurately corrected
Solution Approach 1:
The patent segments the digital image into multiple user images and identifies individual users within the image. Each user image is then processed separately for skin tone correction, allowing accurate detection and correction of individual skin tones rather than applying a single correction to the entire image. This segmentation enables precise measurement of each user's skin tone while maintaining manageable processing complexity through automated user identification algorithms.
Solution Approach 2:
The patent applies local quality by performing skin tone correction on individual user images rather than the entire digital image. Each user image receives customized color correction based on their specific skin tone characteristics, allowing different parts of the image (different users) to have different correction parameters. This ensures accurate skin tone correction for each individual while the system manages complexity through focused local processing.
2Manufacturing precision
If AI-based individual user detection and correction is implemented, then accurate skin tone correction for each user is achieved, but the processing time and computational resources increase
Solution Approach 1:
The patent implements preliminary action by automatically detecting and identifying individual users in the digital image before applying skin tone correction. The system pre-processes the image to segment user images and determine which users require correction, so that when correction is applied, it can be done efficiently with minimal additional processing time. This preliminary user identification and segmentation prepares the image for rapid individualized correction.
Solution Approach 2:
The patent applies parameter changes by adjusting color correction parameters specifically for each detected user image based on their skin tone characteristics. The system modifies hue, saturation, and brightness parameters individually for each user rather than applying uniform correction. This targeted parameter adjustment achieves high correction precision while optimizing processing time by only modifying parameters for detected users rather than processing the entire image.
Data Source
AI summary
Techniques for skin tone modification in digital images are described. For instance, the described techniques can be implemented to detect that input user skin tone data in a digital image exceeds a threshold variation from target skin tone data associated with a user profile. The input user skin tone data can be modified based at least in part on the target skin tone data to generate modified user skin tone data for the digital image.