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A Multiscale Sub-Pixel Detector for Comers in Camera Calibration Targets

机译:用于相机标定目标的多尺度子像素检测器

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Hessian matrix is an important tool to analysis local characters of images, and detectors based on it are used widely in camera calibration.This paper derives a new representation of Hessian matrix by wavelet transform modulus and furtherer proposed a multiscale sub-pixel corner detector based on Hessian matrix and wavelet. It is expected to detect the corners at different scales and overcome the drawback of the singlescale detectors, which may usually either miss significant corners or detect false corners due to noise. For other kinds of corners besides X-corners mentioned in this paper, relative multiscale detectors based on Hessian matrix can be easily designed in the same way as this article. Computer simulation experiments show that at low noise level our algorithm is slightly more accurate than traditional single scale algorithm, and that at high noise level our algorithm is still robust enough to detect most corners when the traditional detector fails.
机译:Hessian矩阵是分析图像局部特征的重要工具,基于它的检测器被广泛用于相机标定。本文通过小波变换模量推导了Hessian矩阵的新表示形式,并进一步提出了一种基于小波变换的多尺度亚像素角点检测器。黑森州矩阵和小波。期望以不同的比例尺检测拐角并克服单尺度检测器的缺点,该缺陷通常可能会遗漏重要的拐角或由于噪声而检测到虚假的拐角。对于本文中提到的X角以外的其他拐角,可以使用与本文相同的方法轻松地设计基于Hessian矩阵的相对多尺度检测器。计算机仿真实验表明,在低噪声水平下,我们的算法比传统的单标度算法精度更高;在高噪声水平下,当传统检测器发生故障时,我们的算法仍具有足够的鲁棒性以检测大多数拐角。

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