Face Segmentation Refinement via Contour Edge Adjustment
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Solution Overview
Problem
Current image processing techniques fail to accurately segment faces from images due to varying environmental conditions and color similarities between faces and backgrounds, leading to coarse segmentation and subsequent distortion in facial images.
Innovation Solution
A method that performs face detection, obtains a coarse face segmentation region, and adjusts it based on contour edges to achieve a fine face segmentation region, using techniques like wavelet transforms and interpolation to refine the segmentation and enhance image processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If face segmentation is performed based only on luminance cue and skin color cue, then the processing speed is maintained, but the segmentation precision deteriorates due to background illumination and color similarity
Solution Approach 1:
The patent segments the face region refinement process into two distinct stages: first obtaining a coarse face segmentation region using traditional skin color and luminance cues, then performing targeted edge detection and contour optimization on this coarse region. This two-stage segmentation approach improves precision by separating the broad detection phase from the精细 refinement phase, allowing each stage to focus on its strength without being overwhelmed by the entire processing complexity.
Solution Approach 2:
The patent performs preliminary edge detection and contour extraction on the coarse face segmentation region before final refinement. By pre-processing the coarse region to identify potential edge locations and contour characteristics, the system prepares the data structure needed for precise boundary determination, thereby improving final segmentation precision while managing computational complexity through staged processing.
2Manufacturing precision
If coarse face segmentation region is used directly, then the processing time is reduced, but the subsequent image processing quality deteriorates due to distortion
Solution Approach 1:
The patent implements a dynamic refinement process that adaptively adjusts the refinement strategy based on the characteristics of the coarse segmentation region. The system dynamically determines edge detection parameters, contour optimization intensity, and region adjustment magnitude based on local image features and segmentation confidence, thereby achieving high processing quality without uniformly applying intensive processing to all regions, thus managing processing time effectively.
Solution Approach 2:
The patent applies local quality refinement by performing edge detection and contour optimization specifically on the boundary regions of the coarse face segmentation, rather than uniformly processing the entire region. The system identifies areas with high uncertainty or potential distortion and applies intensive refinement only to those local areas, maintaining high image processing quality while reducing overall processing time by avoiding unnecessary computation in already-accurate regions.
3Reliability
If traditional skin color model is used for segmentation, then the algorithm simplicity is maintained, but the reliability deteriorates under varying environmental conditions
Solution Approach 1:
The patent introduces edge detection and contour analysis as intermediary steps between the traditional skin color-based coarse segmentation and the final refined segmentation result. These intermediary processes act as mediators that bridge the gap between simple color-based detection and reliable boundary determination, enhancing segmentation reliability under varying environmental conditions by incorporating structural edge information that complements color cues without requiring a complete redesign of the algorithm.
Solution Approach 2:
The patent creates a composite segmentation approach by combining traditional skin color model results with edge detection outcomes and contour optimization techniques. Rather than relying on a single method, the system integrates multiple segmentation cues (color, edge, contour) into a unified refined segmentation result, thereby improving reliability under diverse environmental conditions while managing algorithm complexity through modular integration of established techniques.
Data Source
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AI summary
The present invention provides a method for image processing, a corresponding apparatus and a computer program product. The method comprises performing face detection of an image, obtaining a coarse face segmentation region of at least one face and a contour edge of the at least one face based on the face detection; and adjusting the coarse face segmentation region based on the contour edge to obtain a fine face segmentation region. By using the method, corresponding apparatus and computer program product of the present invention, the coarse face region in an image can be precisely segmented, which provides a good basis for the subsequent image processing based on the fine face segmentation region.