文章基本信息

标题：A Novel Method for Invariant Image Reconstruction
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作者：Mirosław Pawlak ; Gurmukh Singh Panesar ; Marcin Korytkowski 等
期刊名称：Journal of Artificial Intelligence and Soft Computing Research
电子版ISSN：2083-2567
出版年度：2021
卷号：11
期号：1
页码：69-80
DOI：10.2478/jaiscr-2021-0005
出版社：Walter de Gruyter GmbH
摘要：In this paper we propose a novel method for invariant image reconstruction with the properly selected degree of symmetry. We make use of Zernike radial moments to represent an image due to their invariance properties to isometry transformations and the ability to uniquely represent the salient features of the image. The regularized ridge regression estimation strategy under symmetry constraints for estimating Zernike moments is proposed. This extended regularization problem allows us to enforces the bilateral symmetry in the reconstructed object. This is achieved by the proper choice of two regularization parameters controlling the level of reconstruction accuracy and the acceptable degree of symmetry. As a byproduct of our studies we propose an algorithm for estimating an angle of the symmetry axis which in turn is used to determine the possible asymmetry present in the image. The proposed image recovery under the symmetry constraints model is tested in a number of experiments involving image reconstruction and symmetry estimation.
关键词：object representation ; invariant features ; symmetry ; radial orthogonal moments ; continuous symmetry ; ridge regression