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Log-polar sampling incorporating a novel spatially variant filter to improve object recognition

机译:Log-Polar采样结合了一种新型空间变量滤波器,以改善对象识别

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The Fourier-Mellin transform (FMT) is a method for making images rotation, scale and translation (RST) invariant, with applications in object recognition. It can be implemented in either optical or digital form. However, if the transform is to be performed digitally then there are improvements which can be made to the processing to enhance the result. We suggest that the use of a spatially variant filter to modify the output of the Fourier transform (FT) improves the output of the FMT. This paper explains the need to filter an image by varying amounts, which depends on the spatial position of the filter on the image, before log-polar transformation. The implementation of the filter ensures that pixels are filtered along each circumference which is to be sampled, and that the amount of filtering depends upon the radius of the circumference from the centre of sampling. The implementation of the filter requires little extra complexity in comparison with the log-polar transform, while being able to achieve circumferential filtering of the Fourier transform by mapping pixel coordinates and convolving a 1D mask with a square image. The results which have been obtained show that filtering in this way improves the desired phase correlation peak.
机译:Fourier-Mellin变换(FMT)是一种制作图像旋转,比例和转换(RST)不变的方法,具有对象识别的应用。它可以以光学或数字形式实现。但是,如果要在数字上执行变换,则可以对处理进行改进以增强结果。我们建议使用空间变量滤波器来修改傅立叶变换(FT)的输出改善了FMT的输出。本文解释了通过变化量过滤图像的需要,这取决于图像上的滤波器的空间位置,在逻辑极偏振之前。滤波器的实现确保了像素沿着要采样的每个圆周滤波,并且滤波的量取决于从采样的中心的圆周的半径。滤波器的实现与日志极性变换相比,能够通过映射像素坐标和用正方形图像卷积1D掩模来实现傅里叶变换的周向滤波。已经获得的结果表明,以这种方式过滤改善了所需的相位相关峰值。

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