Adaptively weighted sub-directional two-dimensional linear discriminant analysis for face recognition

Lijun Yan; Jeng-Shyang Pan; Shu-Chuan Chu; Muhammad Khan

doi:10.1016/j.future.2010.11.010

Adaptively weighted sub-directional two-dimensional linear discriminant analysis for face recognition

Lijun Yan
, Jeng-Shyang Pan
, Shu-Chuan Chu
, Muhammad Khan

Research output: Contribution to journal › Article › peer-review

16 Citations (Scopus)

Abstract

A novel image classification algorithm named Adaptively Weighted Sub-directional Two-Dimensional Linear Discriminant Analysis (AWS2DLDA) is proposed in this paper. AWS2DLDA can extract the directional features of images in the frequency domain, and it is applied to face recognition. Some experiments are conducted to demonstrate the effectiveness of the proposed method. Experimental results confirm that the recognition rate of the proposed system is higher than the other popular algorithms.

Original language	English
Pages (from-to)	232-235
Number of pages	4
Journal	Future Generation Computer Systems
Volume	28
Issue number	1
DOIs	https://doi.org/10.1016/j.future.2010.11.010
Publication status	Published - Jan 2012

Keywords

Directional filter banks
Face recognition
Two-dimensional linear discriminant analysis

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10.1016/j.future.2010.11.010

Cite this

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title = "Adaptively weighted sub-directional two-dimensional linear discriminant analysis for face recognition",

abstract = "A novel image classification algorithm named Adaptively Weighted Sub-directional Two-Dimensional Linear Discriminant Analysis (AWS2DLDA) is proposed in this paper. AWS2DLDA can extract the directional features of images in the frequency domain, and it is applied to face recognition. Some experiments are conducted to demonstrate the effectiveness of the proposed method. Experimental results confirm that the recognition rate of the proposed system is higher than the other popular algorithms.",

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AU - Khan, Muhammad

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AB - A novel image classification algorithm named Adaptively Weighted Sub-directional Two-Dimensional Linear Discriminant Analysis (AWS2DLDA) is proposed in this paper. AWS2DLDA can extract the directional features of images in the frequency domain, and it is applied to face recognition. Some experiments are conducted to demonstrate the effectiveness of the proposed method. Experimental results confirm that the recognition rate of the proposed system is higher than the other popular algorithms.

KW - Directional filter banks

KW - Face recognition

KW - Two-dimensional linear discriminant analysis

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DO - 10.1016/j.future.2010.11.010

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Adaptively weighted sub-directional two-dimensional linear discriminant analysis for face recognition

Abstract

Keywords

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