Image Viewpoint Correction Using Extrapolation and Keystone
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Solution Overview
Problem
Existing image correction methods are labor-intensive and inaccurate, requiring manual adjustment of camera angles to correct elevation or depression viewpoints, leading to increased time and cost.
Innovation Solution
An image correction system and method that generates extrapolation line segments based on straight line segments in an image, determining slope values, and applies rotation or keystone corrections to achieve a horizontal viewpoint.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual adjustment of camera angle is used to correct elevation or depression viewpoints, then the image viewpoint can be corrected, but the time cost and labor cost increase significantly
Solution Approach 1:
The patent replaces manual mechanical adjustment of camera angles with an automated image processing system that uses computer vision algorithms to detect straight line segments, calculate slope values, and automatically apply rotation or keystone corrections to achieve horizontal viewpoints without manual intervention
Solution Approach 2:
The system enables self-correction by automatically analyzing the image content, detecting vertical lines in buildings or objects, calculating the required correction angle based on slope values, and applying the appropriate transformation (rotation or keystone correction) without requiring manual operation
2Manufacturing precision
If manual image correction is performed to reduce errors from elevation or depression viewpoints, then the position and quality presentation accuracy improves, but the correction process becomes labor-intensive and time-consuming
Solution Approach 1:
The patent replaces manual image correction operations with an automated processing system that uses computer vision to detect straight line segments, calculates slope values to determine correction needs, and automatically applies rotation or keystone transformations to correct the viewpoint and accurately present workpiece position and quality
Solution Approach 2:
The system uses feedback from slope value calculations of detected straight line segments to automatically determine the appropriate correction angle and transformation type, continuously refining the correction process until the viewpoint is properly horizontalized
3Measurement precision
If camera mounting position is adjusted manually to achieve better viewing angle, then the image accuracy improves, but the adjustment process requires repeated comparison and correction
Solution Approach 1:
The patent replaces complex manual camera positioning adjustments with an automated post-processing system that analyzes captured images, detects straight line segments representing vertical structures, calculates slope values to determine viewpoint deviation, and automatically applies the necessary rotation or keystone corrections to achieve accurate horizontal viewpoints
Data Source
AI summary
An image correction method, applicable to an image to be corrected having two boundary, comprises: extending a first and a second straight line in the image to be corrected to generate a first and a second extended straight line with both of them intersecting the first and second boundary to generate multiple intersection points; performing an extrapolation process based on multiple intersection points, center points of the two boundaries, and a half side length to generate a first and a second extrapolation line, rotating the image to be corrected when the first and second extrapolation lines have different slope values to generate a preliminary corrected image; and performing a Keystone correction process when the first and second extrapolation lines have same slope values or when obtaining the preliminary corrected image to generate a corrected image.