Feature Point Matching Verification via Geometric Intersection Analysis
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Solution Overview
Problem
Existing image feature point matching methods suffer from scale errors, main direction errors, and boundary errors, leading to poor matching results, especially in cases of image deformation, and lack an efficient method to verify the correctness of matching results.
Innovation Solution
A method and apparatus that determine a matching feature point pair between images by creating straight-line equations, calculating intersections, forming valid intersection groups, and using a geometric center point to define a judgment area, thereby verifying the correctness of the matching result through whether the straight line passes through this area.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If feature point matching is performed using local texture information and fixed-shaped sub-areas, then the method is simple and easy to implement, but scale errors, main direction errors, and boundary errors occur leading to poor matching accuracy
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing the geometric relationships (straight-line equations, intersections, and judgment areas) between corresponding feature points in the training phase. This pre-computed geometric constraint information is then used during matching to quickly verify candidate pairs without complex real-time calculations, thus maintaining simplicity while improving accuracy
Solution Approach 2:
The patent replaces the traditional mechanical approach of fixed-shaped sub-area division with a mathematical model based on straight-line equations and geometric intersections. By substituting the geometric verification mechanism with algebraic calculations and intersection analysis, the system achieves more accurate error detection while maintaining computational efficiency
2Ease of manufacture
If traditional feature matching descriptors are used, then the implementation is straightforward, but the resolving power of the descriptor deteriorates under image deformation
Solution Approach 1:
The patent introduces a new verification dimension by adding geometric constraint checks (straight-line relationships and judgment area intersections) to the traditional descriptor matching process. This additional dimensional verification layer enables the system to detect and filter out incorrect matches caused by deformation, thereby improving adaptability without complicating the core descriptor computation
Solution Approach 2:
The patent uses straight-line equations and judgment areas as intermediary geometric constructs to mediate between the descriptor similarity measure and the final matching decision. These intermediaries provide an additional layer of geometric validation that helps distinguish true matches from false matches under deformation, bridging the gap between simplicity and robustness
3Productivity
If no verification method is applied to feature point matching results, then the processing is fast, but the correctness of matching results cannot be ensured
Solution Approach 1:
The patent applies preliminary action by pre-computing and storing the geometric constraint information (straight-line equations, intersection points, and judgment areas) during an offline training phase. This pre-computation allows the online verification process to use simple geometric checks rather than complex calculations, maintaining high processing speed while ensuring matching correctness
Solution Approach 2:
The patent implements a feedback mechanism where the geometric verification results (whether a point pair satisfies the straight-line and judgment area constraints) are fed back to validate or reject the descriptor-based matching candidates. This feedback loop ensures that only geometrically consistent matches are accepted, thereby guaranteeing correctness without significantly impacting processing speed
Data Source
AI summary
Disclosed are a method and an apparatus for processing feature point matching result, the first image and the second image are placed reversely, and the matching feature point pair between the first image and the second image is determined by using the feature point matching algorithm; the straight-line equation between each of the feature point pair is made mathematically, and the intersection between each straight line and other straight line is determined; the valid intersection group and the geometric center point thereof are determined according to the distance between each of the intersection and other intersection; and the judgment area of the feature point pair is determined according to the geometric center point, and whether the feature point pair is a correct matching result or not is determined according to whether a straight line between the feature point pair passes through the judgment area or not.