Discriminant spectral hashing for compact palmprint representation

Ying Cong Chen; Meng Hui Lim; Pong Chi Yuen; Jian Huang Lai

doi:10.1007/978-3-319-02961-0_28

Discriminant spectral hashing for compact palmprint representation

Ying Cong Chen, Meng Hui Lim, Pong Chi Yuen, Jian Huang Lai^*

^*Corresponding author for this work

Department of Computer Science

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

7 Citations (Scopus)

Abstract

When palmprint recognition needs to be run in the device with low processing and small storage capacities, binary representation with low storage overhead, high matching speed and high discrimination power is preferred. However, existing feature extraction methods focus more on matching accuracy than representation compactness, which would result in high storage and operation cost. Inspired by Spectral Hashing that is known for compact-binary-representation extraction in the image retrieval domain, we propose a compact binary feature extraction method called Discriminant Spectral Hashing (DSH). DSH projects the feature to a discriminative subspace and then performs Spectral Hashing to obtain discriminative and compact code. Experiment results on a benchmark palmprint database show that our algorithm outperforms the existing coding-based methods in recognition accuracy with shorter code.

Original language	English
Title of host publication	Biometric Recognition
Subtitle of host publication	8th Chinese Conference, CCBR 2013, Jinan, China, November 16-17, 2013, Proceedings
Editors	Zhenan Sun, Shiguan Shan, Gongping Yang, Jie Zhou, Yunhong Wang, YiLong Yin
Publisher	Springer Cham
Pages	225-232
Number of pages	8
ISBN (Electronic)	9783319029610
ISBN (Print)	9783319029603
DOIs	https://doi.org/10.1007/978-3-319-02961-0_28
Publication status	Published - 2013
Event	2012 International Conference on Service-Oriented Computing, ICSOC 2012 - Jinan, China Duration: 16 Nov 2013 → 17 Nov 2013

Publication series

Name	Lecture Notes in Computer Science
Volume	8232
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Name	Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)

Name	CCBR: Chinese Conference on Biometric Recognition

Conference

Conference	2012 International Conference on Service-Oriented Computing, ICSOC 2012
Country/Territory	China
City	Jinan
Period	16/11/13 → 17/11/13

Scopus Subject Areas

Theoretical Computer Science
Computer Science(all)

User-Defined Keywords

Compact palmprint representation
Discriminant spectral hashing
Palmprint recognition

Access to Document

10.1007/978-3-319-02961-0_28

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Chen, Y. C., Lim, M. H., Yuen, P. C., & Lai, J. H. (2013). Discriminant spectral hashing for compact palmprint representation. In Z. Sun, S. Shan, G. Yang, J. Zhou, Y. Wang, & Y. Yin (Eds.), Biometric Recognition: 8th Chinese Conference, CCBR 2013, Jinan, China, November 16-17, 2013, Proceedings (pp. 225-232). (Lecture Notes in Computer Science; Vol. 8232), (Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)), (CCBR: Chinese Conference on Biometric Recognition). Springer Cham. https://doi.org/10.1007/978-3-319-02961-0_28

Chen, Ying Cong ; Lim, Meng Hui ; Yuen, Pong Chi et al. / Discriminant spectral hashing for compact palmprint representation. Biometric Recognition: 8th Chinese Conference, CCBR 2013, Jinan, China, November 16-17, 2013, Proceedings. editor / Zhenan Sun ; Shiguan Shan ; Gongping Yang ; Jie Zhou ; Yunhong Wang ; YiLong Yin. Springer Cham, 2013. pp. 225-232 (Lecture Notes in Computer Science). (Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)). (CCBR: Chinese Conference on Biometric Recognition).

@inproceedings{95cb458366ac4c0b85a364305e715efa,

title = "Discriminant spectral hashing for compact palmprint representation",

abstract = "When palmprint recognition needs to be run in the device with low processing and small storage capacities, binary representation with low storage overhead, high matching speed and high discrimination power is preferred. However, existing feature extraction methods focus more on matching accuracy than representation compactness, which would result in high storage and operation cost. Inspired by Spectral Hashing that is known for compact-binary-representation extraction in the image retrieval domain, we propose a compact binary feature extraction method called Discriminant Spectral Hashing (DSH). DSH projects the feature to a discriminative subspace and then performs Spectral Hashing to obtain discriminative and compact code. Experiment results on a benchmark palmprint database show that our algorithm outperforms the existing coding-based methods in recognition accuracy with shorter code.",

keywords = "Compact palmprint representation, Discriminant spectral hashing, Palmprint recognition",

author = "Chen, {Ying Cong} and Lim, {Meng Hui} and Yuen, {Pong Chi} and Lai, {Jian Huang}",

year = "2013",

doi = "10.1007/978-3-319-02961-0_28",

language = "English",

isbn = "9783319029603",

series = "Lecture Notes in Computer Science",

publisher = "Springer Cham",

pages = "225--232",

editor = "Zhenan Sun and Shiguan Shan and Gongping Yang and Jie Zhou and Yunhong Wang and YiLong Yin",

booktitle = "Biometric Recognition",

}

Chen, YC, Lim, MH, Yuen, PC & Lai, JH 2013, Discriminant spectral hashing for compact palmprint representation. in Z Sun, S Shan, G Yang, J Zhou, Y Wang & Y Yin (eds), Biometric Recognition: 8th Chinese Conference, CCBR 2013, Jinan, China, November 16-17, 2013, Proceedings. Lecture Notes in Computer Science, vol. 8232, Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP), CCBR: Chinese Conference on Biometric Recognition, Springer Cham, pp. 225-232, 2012 International Conference on Service-Oriented Computing, ICSOC 2012, Jinan, China, 16/11/13. https://doi.org/10.1007/978-3-319-02961-0_28

Discriminant spectral hashing for compact palmprint representation. / Chen, Ying Cong; Lim, Meng Hui; Yuen, Pong Chi et al.
Biometric Recognition: 8th Chinese Conference, CCBR 2013, Jinan, China, November 16-17, 2013, Proceedings. ed. / Zhenan Sun; Shiguan Shan; Gongping Yang; Jie Zhou; Yunhong Wang; YiLong Yin. Springer Cham, 2013. p. 225-232 (Lecture Notes in Computer Science; Vol. 8232), (Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)), (CCBR: Chinese Conference on Biometric Recognition).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

TY - GEN

T1 - Discriminant spectral hashing for compact palmprint representation

AU - Chen, Ying Cong

AU - Lim, Meng Hui

AU - Yuen, Pong Chi

AU - Lai, Jian Huang

PY - 2013

Y1 - 2013

N2 - When palmprint recognition needs to be run in the device with low processing and small storage capacities, binary representation with low storage overhead, high matching speed and high discrimination power is preferred. However, existing feature extraction methods focus more on matching accuracy than representation compactness, which would result in high storage and operation cost. Inspired by Spectral Hashing that is known for compact-binary-representation extraction in the image retrieval domain, we propose a compact binary feature extraction method called Discriminant Spectral Hashing (DSH). DSH projects the feature to a discriminative subspace and then performs Spectral Hashing to obtain discriminative and compact code. Experiment results on a benchmark palmprint database show that our algorithm outperforms the existing coding-based methods in recognition accuracy with shorter code.

AB - When palmprint recognition needs to be run in the device with low processing and small storage capacities, binary representation with low storage overhead, high matching speed and high discrimination power is preferred. However, existing feature extraction methods focus more on matching accuracy than representation compactness, which would result in high storage and operation cost. Inspired by Spectral Hashing that is known for compact-binary-representation extraction in the image retrieval domain, we propose a compact binary feature extraction method called Discriminant Spectral Hashing (DSH). DSH projects the feature to a discriminative subspace and then performs Spectral Hashing to obtain discriminative and compact code. Experiment results on a benchmark palmprint database show that our algorithm outperforms the existing coding-based methods in recognition accuracy with shorter code.

KW - Compact palmprint representation

KW - Discriminant spectral hashing

KW - Palmprint recognition

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AN - SCOPUS:84893031853

SN - 9783319029603

T3 - Lecture Notes in Computer Science

SP - 225

EP - 232

BT - Biometric Recognition

A2 - Sun, Zhenan

A2 - Shan, Shiguan

A2 - Yang, Gongping

A2 - Zhou, Jie

A2 - Wang, Yunhong

A2 - Yin, YiLong

PB - Springer Cham

T2 - 2012 International Conference on Service-Oriented Computing, ICSOC 2012

Y2 - 16 November 2013 through 17 November 2013

ER -

Chen YC, Lim MH, Yuen PC, Lai JH. Discriminant spectral hashing for compact palmprint representation. In Sun Z, Shan S, Yang G, Zhou J, Wang Y, Yin Y, editors, Biometric Recognition: 8th Chinese Conference, CCBR 2013, Jinan, China, November 16-17, 2013, Proceedings. Springer Cham. 2013. p. 225-232. (Lecture Notes in Computer Science). (Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)). (CCBR: Chinese Conference on Biometric Recognition). doi: 10.1007/978-3-319-02961-0_28

Discriminant spectral hashing for compact palmprint representation

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