Face Image Processing with Skin Region Segmentation
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Solution Overview
Problem
Existing face image processing technologies fail to effectively differentiate between skin and non-skin regions in faces, leading to unnatural or fake facial processing effects, and do not cater to the varied beautification requirements of different individuals based on attributes like gender, age, and race.
Innovation Solution
A face image processing method and apparatus that perform face detection and attribute analysis to distinguish between skin and non-skin regions, allowing for targeted image processing based on face attribute information, such as gender, age, and race, to provide personalized beautification and enhancement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If face image processing is performed without differentiating between skin and non-skin regions, then processing speed is maintained, but processing accuracy and naturalness deteriorate
Solution Approach 1:
The patent segments the face image into distinct skin regions and non-skin regions using region differentiation technology. This segmentation allows the system to apply different processing strategies to different parts of the face, improving processing accuracy by treating skin areas (which require natural texture preservation) differently from non-skin areas (which can undergo more aggressive enhancement). The segmentation is achieved through analyzing pixel characteristics and spatial relationships without requiring complex manual intervention.
Solution Approach 2:
The patent implements local quality by applying different processing parameters and algorithms to different regions of the face image. Skin regions receive processing that preserves natural texture and avoids over-smoothing, while non-skin regions can undergo different enhancement techniques. This localized approach improves overall processing accuracy while maintaining efficiency by not applying uniform complex processing to the entire image.
2Measurement precision
If uniform image processing is applied to the entire face, then processing simplicity is maintained, but processing accuracy and naturalness deteriorate
Solution Approach 1:
The patent applies local quality by customizing processing parameters for different face regions based on individual attributes. The system analyzes face attributes (such as age, gender, skin type) and adjusts processing intensity and methods for skin regions accordingly. For example, younger skin may receive different processing than mature skin, ensuring natural results that adapt to individual characteristics rather than applying a one-size-fits-all approach.
Solution Approach 2:
The patent utilizes parameter changes by dynamically adjusting processing parameters based on detected face attributes. The system modifies parameters such as smoothing intensity, enhancement strength, and region boundaries according to the specific characteristics of each face being processed. This allows the same processing system to adapt to diverse individual requirements while maintaining high processing accuracy through attribute-based parameter optimization.
3Measurement precision
If region differentiation processing is applied to skin and non-skin regions, then processing accuracy and naturalness are improved, but processing complexity increases
Solution Approach 1:
The patent implements segmentation by automatically dividing the face image into skin and non-skin regions through algorithmic analysis of pixel characteristics, spatial relationships, and color information. This automated segmentation reduces processing complexity compared to manual region definition while maintaining high processing accuracy. The system identifies region boundaries and characteristics without requiring complex user intervention or post-processing adjustment.
Data Source
AI summary
A face image processing method includes: performing face detection on an image to be processed, and obtaining at least one face region image included in the image to be processed and face attribute information in the at least one face region image; and for the at least one face region image, processing an image corresponding to a first region and/or an image corresponding to a second region in the face region image at least according to the face attribute information in the face region image, wherein the first region is a skin region, and the second region includes at least a non-skin region.