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Radial Projection Fourier Transform and its Application for Scene Matching with Rotation Invariance

机译:径向投影傅立叶变换及其在旋转不变场景匹配中的应用

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Scene matching is used for image registration in many fields. There are usually translation and an arbitrary unknown rotation angle between reference and template images. The corresponding scene matching algorithm costs far more computing time than that with small rotation angle and translation. Conceptions of generalized vector image, gray-scale image rotation transformation, gray-scale image point transformation, nature of shift invariance and rotation invariance are proposed to form the foundation of this paper. Radial Projection Fourier Transform (RPFT) is proposed and its rotation invariance is formal proved in this paper. It is applied to the Algorithm of Scene Matching with Rotation Invariance (ASMRI). Calculation on reference and template images can be done separately. Some works can be done before the template images are required. This can improve the matching speed at the cost of more memory. A program to implement the proposed RPFT and ASMRI based on RPFT is coded by means of Visual C++ 6.0. The results prove that ASMRI based on RPFT is not only rotation invariant, but also more accurate and faster than traditional methods. The program can be carried out with hardware.
机译:场景匹配用于许多领域的图像配准。参考图像和模板图像之间通常存在平移以及任意未知的旋转角度。相应的场景匹配算法比小旋转角度和平移的算法花费更多的计算时间。提出了广义矢量图像,灰度图像旋转变换,灰度图像点变换,位移不变性和旋转不变性的概念,为本文奠定了基础。提出了径向投影傅立叶变换(RPFT),并对其旋转不变性进行了形式证明。应用于具有旋转不变性的场景匹配算法(ASMRI)。参考图像和模板图像的计算可以分别进行。在需要模板图像之前,可以完成一些工作。这样可以提高匹配速度,但需要更多的内存。使用Visual C ++ 6.0编写了一个程序,以实现建议的RPFT和基于RPFT的ASMRI。结果证明,基于RPFT的ASMRI不仅旋转不变,而且比传统方法更准确,更快。该程序可以用硬件执行。

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