Focus Evaluator for Image Content Analysis
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Solution Overview
Problem
Conventional image processing systems fail to accurately represent the overall focus of an image due to the inclusion of background regions, which can result in a lower focus quality value even if the region of interest is in focus, as they consider both high-focus and low-focus regions when generating an overall focus value.
Innovation Solution
A focus evaluator that categorizes image content into different groupings based on focus values and compares their sizes to identify the most representative grouping, generating an overall focus value based on the high-focus regions, thereby isolating the impact of background regions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional image processing systems process all pixels from high-focus and low-focus regions to generate an overall focus value, then the focus evaluation covers the entire image, but the resulting overall focus value is not representative of the image's actual focus quality because it is penalized by blurry background regions
Solution Approach 1:
The patent segments the image into multiple regions based on focus characteristics, distinguishing between high-focus regions (foreground) and low-focus regions (background). This segmentation allows the system to evaluate focus quality separately for different image portions, preventing blurry backgrounds from penalizing the overall focus assessment of the main subject.
Solution Approach 2:
The patent applies different evaluation criteria to different regions of the image. High-focus regions are weighted more heavily in the overall focus assessment, while low-focus regions are either excluded or given minimal weight. This local quality approach ensures that the focus evaluation reflects the actual quality of the main subject rather than being averaged down by intentional background blur.
2Reliability
If the overall focus value is based on all pixels from high-focus regions and low-focus regions, then the evaluation is comprehensive, but images with focused foreground are incorrectly assigned a lower focus quality value due to the presence of blurry background
Solution Approach 1:
The patent extracts and isolates the high-focus regions from the low-focus background regions. By separating these components, the system can generate the overall focus value based primarily on the high-focus regions that contain the main subject, effectively taking out the detrimental influence of blurry background areas from the focus quality assessment.
Solution Approach 2:
Instead of evaluating the entire image uniformly as conventional systems do, the patent inverts the approach by focusing evaluation primarily on the high-focus regions and minimizing or excluding low-focus regions. This inversion ensures that the focus quality indication accurately reflects the sharpness of the main subject rather than being dominated by the inevitable blur in background areas.
Data Source
AI summary
Embodiments herein include a focus evaluator configured to categorize portions of image content into different groupings depending on a respective focus value derived for each portion of the image content. The focus evaluator compares relative sizes of the different groupings to identify one or more groupings representative of an overall focus quality associated with the image content. Based on the identified one or more groupings, the focus evaluator generates the overall focus value for the image content.