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Frontiers of Information Technology & Electronic Engineering  1998 Vol.-1 No.-1 P.

10.1631/FITEE.1900552


Subspace transform-induced robust similarity measure for facial images


Author(s):  Jian ZHANG, Heng ZHANG, Li-ling BO, Hong-ran LI, Shuai XU, Dong-qing YUAN

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

Corresponding email(s):   zhangjian@jou.edu.cn, zhangheng@jou.edu.cn

Key Words:  Subspace analysis, Image similarity measure, Face recognition, Pattern recognition


Jian ZHANG, Heng ZHANG, Li-ling BO, Hong-ran LI, Shuai XU, Dong-qing YUAN. Subspace transform-induced robust similarity measure for facial images[J]. Frontiers of Information Technology & Electronic Engineering, 1998, -1(-1): .

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author="Jian ZHANG, Heng ZHANG, Li-ling BO, Hong-ran LI, Shuai XU, Dong-qing YUAN",
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doi="10.1631/FITEE.1900552"
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Abstract: 
The similarity measure has long played a critical role and attracted great research interest in various areas such as pattern recognition and machine perception. Nevertheless, there remains the issue of developing an efficient 2-dimensional robust similarity measure for images. Inspired by the properties of subspace, we develop an effective 2-dimensional image similarity measure technique named transformation similarity measure (TSM) for robust face recognition. Specifically, the proposed TSM robustly determines the similarity between two well-aligned frontal facial images while weakening some interference in face recognition by linear transformation and singular value decomposition. We present the mathematical features and some odds to reveal the feasible and robust measure mechanism of the TSM. The performance of the proposed similarity measure method, combined with the nearest neighbor rule, is evaluated in face recognition under different challenges. The experimental results clearly show the advantages of the TSM in accuracy and robustness.

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