The application of central projection transform combines region-based methods with contour-based methods

and it is an effective invariant feature extraction algorithm. However

current literature lacks of further discussion of robustness to noise

and only a few simple theoretical and experimental results can be found. In this paper

we mainly study the robustness to noise of central projection transformation. Using the ideas of analysis for the robustness to noise of Radon transformation

we discuss the robustness to noise of central projection transformation. Theoretical results show that central projection transform is very robust to white noise and salt and pepper noise

and its robustness is affected by the size of the input noise image

the percentage of the shape region

and the level of noise. Theoretical analytic and experiment results show that central projection transform is very robust to white noise and salt and pepper noise

and its robustness is affected to on the size of the input noise image

the percentage of the shape region

and the level of noise.