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c# - 比较倾斜度数的图像

转载 作者:太空狗 更新时间:2023-10-29 17:55:36 26 4
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我有一个问题,如下所示,上面的是原始图像,下面的是向左倾斜 90 度的图像。有没有办法计算角度的变化。我试过霍夫变换,我可以检测到位置,但是我无法检测到改变的天使。是否有替代方法来检测度数变化。

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最佳答案

我在使用对称的仅相位匹配滤波器之前已经完成了这项工作。它实际上是用于指纹识别,允许旋转和缩放。不幸的是,它非常复杂。您需要熟悉如何计算 FFT 和类似级别的数学。我不是在 C# 中做的,而是在 MATLAB 中(以及在可综合的 Verilog 中,但这完全是另一回事)。我建议首先使用 MATLAB 或类似的数学包,以确保您的算法正确。

不过,希望有人已经在某处的 .NET 图像处理库中实现了该算法。

我使用的纸张如下。它更基于数学而非算法,因此需要一些工作才能将其转换为代码:

Qin-Sheng Chen; Defrise, M.; Deconinck, F. "Symmetric phase-only matched filtering of Fourier-Mellin transforms for image registration and recognition," Pattern Analysis and Machine Intelligence, IEEE Transactions on , vol.16, no.12, pp.1156-1168, Dec 1994

Abstract: Presents a new method to match a 2D image to a translated, rotated and scaled reference image. The approach consists of two steps: the calculation of a Fourier-Mellin invariant (FMI) descriptor for each image to be matched, and the matching of the FMI descriptors. The FMI descriptor is translation invariant, and represents rotation and scaling as translations in parameter space. The matching of the FMI descriptors is achieved using symmetric phase-only matched filtering (SPOMF). The performance of the FMI-SPOMF algorithm is the same or similar to that of phase-only matched filtering when dealing with image translations. The significant advantage of the new technique is its capability to match rotated and scaled images accurately and efficiently. The innovation is the application of SPOMF to the FMI descriptors, which guarantees high discriminating power and excellent robustness in the presence of noise. This paper describes the principle of the new method and its discrete implementation for either image detection problems or image registration problems. Practical results are presented for various applications in medical imaging, remote sensing, fingerprint recognition and multiobject identification

关于c# - 比较倾斜度数的图像,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/4969947/

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