Fisheye Lens Image Conversion for Panoramic Monitoring
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Solution Overview
Problem
Omnidirectional monitoring cameras using fisheye lenses face challenges in converting images into panoramic form due to magnification distortion, especially in peripheral regions, where correction accuracy is unstable due to factors like dome degradation or nighttime IR light emission, leading to noticeable errors and reduced image quality.
Innovation Solution
An imaging apparatus and method that performs geometrical conversion on fisheye images, where regions closer to the optical axis are converted to perspective projection and those farther away are converted to stereographic projection, with a set distance determined by the accuracy of fisheye lens distortion correction, to balance straight line reproducibility and error suppression in peripheral areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the entire fisheye image is converted to perspective projection, then straight line reproducibility is improved, but magnification distortion occurs in peripheral regions
Solution Approach 1:
The image is divided into two regions: a central region (within the first predetermined distance from the optical axis) converted to perspective projection for accurate straight line reproduction, and a peripheral region (beyond the first predetermined distance) converted to stereographic projection to avoid magnification distortion. This segmentation allows each region to use the most appropriate projection method for its characteristics.
Solution Approach 2:
Different projection methods are applied to different regions of the image based on their specific requirements. The central region requires perspective projection for straight line accuracy, while the peripheral region requires stereographic projection for shape preservation. This local optimization resolves the contradiction by allowing each region to have its own quality characteristics.
2Measurement precision
If strong correction is applied to bring object shapes closer to homothetic forms, then shape accuracy is improved, but errors are amplified in peripheral regions due to lens distortion correction instability
Solution Approach 1:
The correction intensity is varied by region: strong correction is applied in the central region where lens distortion is more stable and predictable, while weak or no correction is applied in the peripheral region where lens distortion correction is less reliable. This resolves the contradiction by adapting correction strength to local reliability conditions.
Solution Approach 2:
The image is segmented into central and peripheral regions with different correction strategies. The central region receives aggressive shape correction to achieve homothetic accuracy, while the peripheral region receives minimal correction to avoid amplifying unstable distortion errors. This segmentation allows simultaneous optimization of shape accuracy and correction stability.
3Measurement precision
If fisheye lens distortion correction is performed with high intensity, then straight line components are more accurately reproduced, but errors become noticeable in peripheral regions due to dome degradation or nighttime IR light emission
Solution Approach 1:
The image is divided into central and peripheral regions with different projection methods. The central region uses perspective projection for accurate straight line reproduction, while the peripheral region uses stereographic projection to minimize noticeable errors. This segmentation resolves the contradiction by allowing each region to be optimized for its specific requirements.
Solution Approach 2:
Instead of attempting to correct all distortion uniformly (which amplifies errors in peripheral regions), the patent accepts that peripheral regions have inherent distortion limitations and uses stereographic projection there, which is better suited for capturing the wide field of view despite some distortion. This converts the limitation into a beneficial approach for the peripheral region.
Data Source
AI summary
There is provided with an imaging apparatus. An imaging unit captures an image with use of a fisheye lens. An image conversion unit converts an input image obtained from the imaging unit into a panoramic image, by performing geometrical conversion on the input image such that a region of the input image in which a distance from a point on an optical axis is smaller than a set distance becomes a perspective projection, and such that a region in which the distance is larger than the set distance becomes a stereographic projection. The set distance is determined based on an accuracy of fisheye lens distortion correction with respect to the fisheye lens.