Subspace transform induced robust similarity measure for facial images

2020年第21卷第9期

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《信息与电子工程前沿（英文）》 >> 2020年第21卷第9期 doi: 10.1631/FITEE.1900552

Subspace transform induced robust similarity measure for facial images

Affiliation(s): Department of Computer Engineering, Jiangsu Ocean University, Lianyungang 222005, China; Department of Mathematics, Jiangsu Ocean University, Lianyungang 222005, China; less

收稿日期： 2019-10-11 录用日期： 2020-09-09 发布日期： 2020-09-09

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摘要

Similarity measure has long played a critical role and attracted great interest in various areas such as and machine perception. Nevertheless, there remains the issue of developing an efficient two-dimensional (2D) robust similarity measure method for images. Inspired by the properties of subspace, we develop an effective 2D technique, named transformation similarity measure (TSM), for robust . Specifically, the TSM method robustly determines the similarity between two well-aligned frontal facial images while weakening interference in the by linear transformation and singular value decomposition. We present the mathematical features and some odds to reveal the feasible and robust measure mechanism of TSM. The performance of the TSM method, combined with the nearest neighbor rule, is evaluated in under different challenges. Experimental results clearly show the advantages of the TSM method in terms of accuracy and robustness.