Local Structure-Based Image Decomposition for Feature Extraction With Applications to Face Recognition
- Creators
- Qian, Jianjun
- Yang, Jian
- Xu, Yong
Abstract
This paper presents a robust but simple image feature extraction method, called image decomposition based on local structure (IDLS). It is assumed that in the local window of an image, the macro-pixel (patch) of the central pixel, and those of its neighbors, are locally linear. IDLS captures the local structural information by describing the relationship between the central macro-pixel and its neighbors. This relationship is represented with the linear representation coefficients determined using ridge regression. One image is actually decomposed into a series of sub-images (also called structure images) according to a local structure feature vector. All the structure images, after being down-sampled for dimensionality reduction, are concatenated into one super-vector. Fisher linear discriminant analysis is then used to provide a low-dimensional, compact, and discriminative representation for each super-vector. The proposed method is applied to face recognition and examined using our real-world face image database, NUST-RWFR, and five popular, publicly available, benchmark face image databases (AR, Extended Yale B, PIE, FERET, and LFW). Experimental results show the performance advantages of IDLS over state-of-the-art algorithms.
Additional Information
© 2013 IEEE. Manuscript received July 15, 2011; revised November 11, 2011, March 27, 2012, July 16, 2012, January 9, 2013, and April 10, 2013; accepted May 8, 2013. Date of publication May 22, 2013; date of current version August 9, 2013. This work was supported in part by the National Science Fund for Distinguished Young Scholars under Grant 61125305 and Grant 61233011, the Key Project of Chinese Ministry of Education. The associate editor coordinating the review of this manuscript and approving it for publication was Prof. Bulent Sankur.Additional details
- Eprint ID
- 41967
- Resolver ID
- CaltechAUTHORS:20131017-100945011
- 61125305
- National Science Fund for Distinguished Young Scholars
- 61233011
- National Science Fund for Distinguished Young Scholars
- Chinese Ministry of Education Key Project
- Created
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2013-10-17Created from EPrint's datestamp field
- Updated
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2021-11-10Created from EPrint's last_modified field
- Other Numbering System Name
- INSPEC Accession Number
- Other Numbering System Identifier
- 13696761