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.