Lens Distortion Self-Calibration Using the Hough Transform

D. Bailey, Yuan Chang, S. L. Moan
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引用次数: 1

Abstract

The Hough transform is a well known technique for detecting straight lines within images, especially in the presence of noise, or where there is incomplete data (gaps or occlusions). When subjected to lens distortion, straight lines become curved, and indeed this can be used to identify and correct lens distortion. However, curved lines distort and blur the peaks within the Hough transform, making the lines more difficult to detect. However, by analysing the distortion within the Hough transform, it is possible to directly estimate the lens distortion parameters enabling the distortion to be corrected in real time. The proposed technique uses a Terasic DE1-SoC FPGA board (Cyclone V FPGA) to fit a parabola to the distorted peak using Hough's original transform, and from the parabola coefficients directly estimates the lens distortion parameter. This enables the following frame to be corrected in parallel with curve detection.
基于霍夫变换的透镜畸变自校正
霍夫变换是一种众所周知的检测图像中直线的技术,特别是在存在噪声或存在不完整数据(间隙或遮挡)的情况下。当受到透镜畸变时,直线变成弯曲,这确实可以用来识别和纠正透镜畸变。然而,曲线扭曲和模糊了霍夫变换中的峰值,使得线条更难以检测。然而,通过分析霍夫变换中的畸变,可以直接估计透镜畸变参数,从而实时校正畸变。该技术采用Terasic DE1-SoC FPGA板(Cyclone V FPGA),利用霍夫原始变换将抛物线拟合到畸变峰上,并从抛物线系数直接估计透镜畸变参数。这使得以下帧可以与曲线检测并行进行校正。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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