Image Processing Key Point Selection for Perspective Correction
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Solution Overview
Problem
Existing image processing methods face challenges in accurately recognizing and correcting target areas in captured images due to low accuracy in target area recognition, leading to poor image correction effects and user experience.
Innovation Solution
An image processing method that performs key point detection to determine key point combinations, allowing users to select a target key point combination for perspective distortion correction, thereby improving the accuracy of target area recognition and correction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated target area recognition is performed using existing methods, then the processing speed is improved, but the recognition accuracy deteriorates
Solution Approach 1:
The patent segments the target area recognition process into multiple independent stages: key point detection, key point combination generation, user selection, and distortion correction. This segmentation allows each stage to be optimized independently, with automated key point detection maintaining speed while user selection ensures accuracy.
Solution Approach 2:
The patent performs preliminary key point detection and generates multiple key point combinations before user selection. This preliminary automated processing speeds up the workflow by preparing candidate solutions, while the user then selects from these preprocessed options to ensure accuracy.
2Measurement precision
If user interaction is added for key point combination selection, then the recognition accuracy is improved, but the operation complexity increases
Solution Approach 1:
The system performs self-service by automatically detecting key points and generating multiple key point combinations for user selection. This reduces the burden on the user compared to manual key point marking, while still allowing user input for final selection to ensure accuracy.
Solution Approach 2:
The patent changes the interaction parameter from manual key point marking to selecting from pre-generated key point combinations. This parameter change simplifies user operation while maintaining recognition accuracy, as users only need to select from predefined options rather than create selections from scratch.
3Measurement precision
If multiple key point combinations are generated for user selection, then the correction accuracy is improved, but the device complexity increases
Solution Approach 1:
The patent implements a dynamic system that generates multiple key point combinations based on detected key points, allowing the system to adapt to different image scenarios. This dynamic generation process improves correction accuracy by providing multiple candidates, while the algorithmic nature keeps complexity manageable.
Solution Approach 2:
The patent introduces key point combinations as an intermediary between key point detection and distortion correction. This intermediary layer allows the system to maintain simplicity in individual components while achieving high overall accuracy through the intermediate selection step.
Data Source
AI summary
An image processing method includes: performing key point detection on an image to-be-processed, to determine a plurality of key points in the image to-be-processed which are corner points in the image to-be-processed; determining at least one key point combination among the plurality of key points, wherein each of the at least one key point combination includes four key points used to define a quadrilateral object; in response to a key point combination selection instruction input by a user, determining a target key point combination in the at least one key point combination; and performing perspective distortion correction on a quadrilateral area defined by a quadrilateral object corresponding to the target key point combination on the image to-be-processed, to obtain a processed image.