Region Correction Device for Image Analysis
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Solution Overview
Problem
Existing image analysis techniques face challenges in accurately detecting regions of predetermined subjects in images due to errors caused by shadows and distortion, leading to incorrect detection of line segments and increased calculation costs.
Innovation Solution
A region correction device and method that extracts line segments from prediction regions using a line segment extraction unit and corrects these regions based on the extracted segments, outputting corrected prediction region information to improve detection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If the entire image is corrected by fitting to a distortion model, then the linearity of character lines is improved, but the calculation cost increases and the shape of the subject image is distorted
Solution Approach 1:
The patent divides the correction process into two independent stages: first detecting line segments in the binarized image, then correcting only the grayscale image using these extracted line segments as constraints. This segmentation avoids the need to correct the entire image while maintaining computational efficiency and preserving subject image shape.
Solution Approach 2:
The patent extracts line segment information from the binarized image separately from the grayscale image correction process. By taking out the line segment detection as a preliminary step, the system can use these extracted segments to guide the grayscale correction without reprocessing the entire image, thereby reducing calculation cost.
2Manufacturing precision
If the entire image is corrected by fitting to a distortion model, then the linearity of character lines is improved, but the shape of the subject image is distorted
Solution Approach 1:
The patent segments the correction process into binarized image processing (for linearity) and grayscale image processing (for shape preservation). By handling these separately and using line segment constraints rather than global distortion models, the system achieves linear character lines without distorting the subject image shape.
Solution Approach 2:
The patent applies different correction qualities to different parts of the image: the binarized image is corrected for linearity using line segment fitting, while the grayscale image is corrected locally based on constraints from extracted line segments. This local quality approach preserves the overall shape of the subject image while achieving linearity where needed.
3Device complexity
If line segments are detected in the image, then the detection process is simplified, but the line segments are not corrected and region detection accuracy is reduced
Solution Approach 1:
The patent uses the detected line segments as feedback constraints to guide the grayscale image correction process. The line segments detected in the binarized image provide feedback that constrains the correction of the grayscale image, ensuring that region detection accuracy is maintained while keeping the detection process simplified.
Solution Approach 2:
The patent performs preliminary detection of line segments in the binarized image before correcting the grayscale image. This preliminary action extracts the necessary geometric constraints that will be used during the subsequent grayscale correction, ensuring both simplified detection and high accuracy without requiring complex simultaneous processing.
Data Source
AI summary
A region correction device (1) according to the present disclosure includes: an input unit (41) that receives an input of prediction region information indicating a prediction region (PA) indicating an image of a predetermined subject, the prediction region (PA) being detected from a captured image obtained by imaging the predetermined subject; a line segment extraction unit (42) that extracts a line segment on the basis of a contour of the prediction region (PA) indicated by the prediction region information; a correction unit (43) that corrects the prediction region (PA) on the basis of the line segment; and an output unit (44) that outputs corrected prediction region information indicating a corrected prediction region, the corrected prediction region being the prediction region (PA) that has been corrected.