Annular Image Distortion Correction via Polar Coordinate Center Shifting
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Solution Overview
Problem
Existing methods for converting annular images into panoramic development images require preliminary reference image data and time-consuming data matching processes to correct optical axis deviations, making them inefficient for variations in products or lens changes.
Innovation Solution
An image processing method that extracts inner and outer circles from annular images, moves a processing center between their centers, and uses polar coordinate conversion to correct distortions, eliminating the need for preliminary reference data and reducing the complexity of data matching processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If data matching process is conducted to correct optical axis deviation, then correction accuracy is improved, but processing time is increased
Solution Approach 1:
The invention extracts the inner circle and outer circle from the annular image to obtain their centers, which serve as reference points for correction. This extraction approach eliminates the need for time-consuming data matching processes while maintaining correction accuracy, as the circle centers provide sufficient reference information for polar coordinate conversion.
Solution Approach 2:
The method uses the annular image itself to provide correction information by extracting geometric features (inner and outer circles) directly from the image data. This self-service approach eliminates the need for external reference image data or preliminary setup, allowing the system to correct optical axis deviation autonomously without additional time-consuming processes.
2Reliability
If reference image data is prepared preliminarily to correct optical axis deviation, then correction reliability is improved, but operational complexity is increased
Solution Approach 1:
The system uses the annular image itself to provide all necessary correction information by extracting the inner and outer circle centers. This eliminates the need for preliminary reference image data preparation and complex operational procedures, while maintaining reliable correction through the geometric properties of the extracted circles.
Solution Approach 2:
The extracted inner and outer circle centers serve multiple functions: they provide reference points for correction, define the processing range, and enable the polar coordinate conversion. This multi-functional approach simplifies the overall process while maintaining reliability, as the same geometric features serve multiple purposes in the correction pipeline.
3Adaptability or versatility
If data matching process is conducted for each product variation or lens change, then adaptation to variations is improved, but productivity is decreased
Solution Approach 1:
The method extracts correction information directly from each annular image by identifying the inner and outer circle centers, allowing the system to adapt to product variations and lens changes autonomously. This eliminates the need for time-consuming data matching processes for each variation, maintaining adaptability while significantly improving processing efficiency.
Solution Approach 2:
The approach changes from using fixed reference image data to dynamically extracting geometric parameters (circle centers) from each image. This parameter-based approach allows the system to adapt to variations in products and lenses by automatically adjusting to the specific geometric characteristics of each image, thereby maintaining versatility while improving productivity.
Data Source
AI summary
An image processing method includes a step of extracting an inner circle and an outer circle from an annular image, a step of obtaining the center for the extracted inner circle and the extracted outer circle respectively, and a step of moving a processing center serving as a reference in the polar coordinate conversion gradually between the center of the inner circle and the center of the outer circle to convert the circular image into a panoramic development image. According thereto, when an annular image of a side wall surface of a hole imaged by an omnidirectional imaging device (10) is converted into a panoramic development image according to a polar coordinate conversion, a distortion resulted from a position deviation occurred between an optical axis (L1) of the omnidirectional imaging device (10) and a central axis (L2) of the hole (H) can be corrected.