A complete set of pseudo-zernike moment invariants by image shape description

Authors:
Lin Zheng;Sinan Zhao;Qian Liu;Hongqing Zhu
Affiliations:
Department of Electronics and Communications Engineering, East China University of Science and Technology, Shanghai, China;Department of Information and Control Engineering, Shanghai University of Electric Power, Shanghai, China;Department of Electronics and Communications Engineering, East China University of Science and Technology, Shanghai, China;Department of Electronics and Communications Engineering, East China University of Science and Technology, Shanghai, China
Venue:
AICI'12 Proceedings of the 4th international conference on Artificial Intelligence and Computational Intelligence
Year:
2012

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Abstract

Orthogonal moments such as pseudo-Zernike moments have been successfully used in the field of image analysis. Conventionally, image function is mapped onto a set of orthogonal functions over the unit circle. If the origin of polar coordinate system is taken at the centroid, the rotation invariants will be easy to obtain. Based on pseudo-Zernike moments, this paper presents a new method to drive the complete rotation, scaling and translation (RST) invariants from the orthogonal projection transform (OPT). The efficiency and the robustness to different noises of the method for classification tasks are presented by comparing it with several existing methods.