Template Mark Detection Using Single Camera and Linear Fitting
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Solution Overview
Problem
Conventional methods for template mark detection using a single camera face challenges due to limited installation space and low inclination angle accuracy, particularly when using optical correction methods with fixed slope lines and small differences in pixel values, which hinder accurate position determination of marks.
Innovation Solution
A method involving image collection by a single camera, preprocessing to obtain binary images, corner detection of jagged edges, edge and line detection, collinearity judgment, and linear fitting using arctan functions to calculate accurate inclination angles, enabling high-accuracy detection and position correction of template marks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single camera is used for mark detection, then device complexity and installation space requirements are reduced, but measurement precision and inclination angle accuracy deteriorate
Solution Approach 1:
The detection process is segmented into multiple independent stages: image acquisition, binary threshold segmentation, edge detection, line segment extraction, collinearity judgment, and linear fitting. Each stage processes specific features separately, allowing the system to achieve high measurement precision through cumulative refinement while maintaining simple hardware structure
Solution Approach 2:
The solution transitions from 2D image coordinates to 3D spatial relationships by calculating inclination angles through collinearity judgment and linear fitting. This dimensional transformation enables accurate mark detection and position correction without requiring complex multi-camera systems
2Device complexity
If optical correction methods with fixed slope lines are used, then device installation is simplified, but measurement precision and mark slope accuracy deteriorate
Solution Approach 1:
The method replaces fixed slope optical correction with dynamic detection that adapts to actual mark orientations. By detecting edge lines and performing collinearity judgment, the system calculates actual inclination angles and corrects positions dynamically, achieving high slope accuracy without complex fixed-structure devices
Solution Approach 2:
The solution changes the detection parameter from fixed slope assumption to variable inclination angle calculation. Through linear fitting and collinearity judgment, the system determines actual mark orientations and corrects positions based on calculated angles rather than predetermined slopes, significantly improving manufacturing precision
3Device complexity
If gray scale image corner detection is used, then processing is simpler, but measurement precision and number of detected corners deteriorate
Solution Approach 1:
The system performs preliminary binary threshold segmentation and edge detection before corner detection. This preliminary processing enhances edge sharpness and contrast, making corners more distinct and detectable. The subsequent collinearity judgment further refines corner identification, achieving high measurement precision while maintaining manageable processing complexity
Data Source
AI summary
Provided are template mark detection method and template position correction method based on single camera, including: performing image collection on mark on template by single camera, and obtaining binary image after preprocessing; performing corner detection of jagged edges on binary image to obtain corner set of jagged edges; performing edge detection and line detection sequentially on binary image to obtain set of edge line segments from coarse detection; traversing such set, and judging and retaining collinear line segments, to obtain set of collinear line segments from coarse detection; traversing corner set of jagged edges, for point-line collinearity judgment with line segments in set of collinear line segments from coarse detection, to obtain set of point-line from fine detection; and performing linear fitting on set of point-line from fine detection, and calculating an inclination angle of each straight line through an arctan function, thus completing detection of mark.