Image Roughness Compensation for Accurate Shadow Recognition
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Solution Overview
Problem
Existing shadow detection methods based on pixel roughness values are prone to erroneous determinations due to missing pixel data at the edges of images, especially when shooting angles cause loss of pixels far from the shooting apparatus.
Innovation Solution
A method and system that compensates for roughness values by determining the average position information of pixels within a preset compensation region, adjusting roughness values using specific coefficients based on region-specific segmentation thresholds derived from chrominance components, and dynamically segmenting images to reduce erroneous shadow recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If shadow detection is performed using roughness values of pixels in the target region, then shadow recognition can be achieved, but erroneous determination occurs when pixels are lost due to shooting angle
Solution Approach 1:
The patent applies preliminary action by calculating average position information of pixels in the target region before performing shadow detection. This allows the system to proactively identify regions where pixel data may be lost due to shooting angle, and apply roughness value compensation in advance, thereby preventing erroneous shadow recognition rather than correcting it after the fact.
Solution Approach 2:
The patent changes the roughness value parameter by introducing a compensation mechanism. When pixel data is lost, the system modifies the roughness value calculation by incorporating position-based compensation, transforming the original roughness parameter into a compensated roughness parameter that accounts for missing data, thus maintaining shadow detection reliability.
2Measurement precision
If roughness values are calculated using all pixels in the target region, then comprehensive shadow analysis is achieved, but errors occur when pixels far from the shooting apparatus are lost
Solution Approach 1:
The patent applies local quality by differentiating the treatment of pixels based on their position relative to the shooting apparatus. Pixels closer to the shooting apparatus are weighted differently than those farther away, with position-based compensation applied selectively. This local differentiation ensures that regions with complete pixel data contribute more reliably to the roughness calculation while accounting for data loss in distant regions.
Data Source
AI summary
Disclosed are a roughness compensation method and system, an image processing device, and a readable storage medium. The roughness compensation method includes the following steps: acquiring a roughness value of a target region in an image and position information of pixels in the target region; averaging the position information of the pixels in the target region to obtain average position information; determining whether the average position information is located in a preset compensation region; and compensating and updating the roughness value when the average position information is located in the preset compensation region; or skipping compensating the roughness value when the average position information is not located in the preset compensation region. In the present disclosure, a determination result of whether the average position information is located in a preset compensation region is used as a basis of compensation, and a compensated roughness value is used for an image processing program such as shadow recognition, which can effectively reduce erroneous determination of shadow recognition results.