Face Recognition Exposure Adjustment for Backlighting
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Solution Overview
Problem
Human face recognition systems face difficulties in imperfectly illuminated environments, such as back lighting or low ambient light, where they struggle to capture sufficient biological information due to inadequate exposure values, leading to poor recognition performance.
Innovation Solution
An image processing system and method that includes capturing images, executing face detection, adjusting exposure values, analyzing image information, and processing the face area using model parameters to enhance image quality, specifically utilizing techniques like Wide Dynamic Range (WDR) or High Dynamic Range (HDR) technologies to improve face recognition accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If the exposure value is increased to capture more light in low illumination environments, then the brightness of the face area is improved, but the overall image quality deteriorates due to overexposure in other areas
Solution Approach 1:
The patent applies local quality by adjusting the exposure value specifically for the face area (predetermined area) rather than the entire image. The exposure value adjusting unit modifies only the relevant region to achieve proper illumination while preserving the quality of other areas. This is accomplished by identifying the face area through detection and applying targeted exposure adjustment to that specific region.
2Measurement precision
If the exposure value is adjusted to improve face recognition in specific areas, then the recognition accuracy is improved, but the complexity of the image processing system increases
Solution Approach 1:
The patent applies preliminary action by performing face detection and determining the predetermined area before adjusting the exposure value. The system proactively identifies the face area and pre-calculates the appropriate exposure adjustment needed, then applies this adjustment before the actual image capture or processing. This sequential approach (detection → determination → adjustment) simplifies the overall system architecture by breaking down the complex task into manageable preliminary steps.
3Reliability
If multiple image processing operations are performed to enhance face recognition, then the recognition reliability is improved, but the processing time increases
Solution Approach 1:
The patent applies partial action by focusing image processing operations specifically on the predetermined face area rather than processing the entire image. The exposure value adjustment and subsequent processing are confined to the relevant region, achieving sufficient recognition reliability without the computational overhead of processing all image data. This selective approach maintains reliability while reducing processing time.
Data Source
AI summary
An image processing method includes following steps: capturing an image including a human face; executing a face detection in a predetermined area of the image; adjusting an exposure value of the predetermined area to an expected value when the face detection does not recognize the human face; executing the face detection and analyzing an image information in a face area of the image when the exposure value of the predetermined area reaches the expected value; and selecting a model parameter and an image adjusting parameter correspondingly according to the image information, processing the face area of the image, and outputting a processed image to a human face recognition system.