"Non-locality" preserving projection and its application to palmprint recognition

Jian Yang; Dapeng Zhang; Jing Yu Yang

doi:10.1109/ICARCV.2006.345339

"Non-locality" preserving projection and its application to palmprint recognition

Jian Yang
, Dapeng Zhang
, Jing Yu Yang

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

7 Citations (Scopus)

Abstract

This paper develops a "Non-locality" Preserving Projection (NLPP) technique for feature extraction. In contrast to the existing Locality Preserving Projection (LPP), a technique based on the characterization of the local scatter, NLPP is a method based on the characterization of the non-local scatter. Intuitively, NLPP should be more effective than LPP when the non-local information plan a dominant role in discrimination. NLPP is tested using the PolyU palmprint database and the experimental results show that NLPP outperforms PCA, LDA and LPP.

Original language	English
Title of host publication	9th International Conference on Control, Automation, Robotics and Vision, 2006, ICARCV '06
DOIs	https://doi.org/10.1109/ICARCV.2006.345339
Publication status	Published - 1 Dec 2006
Event	9th International Conference on Control, Automation, Robotics and Vision, 2006, ICARCV '06 - Singapore, Singapore Duration: 5 Dec 2006 → 8 Dec 2006

Conference

Conference	9th International Conference on Control, Automation, Robotics and Vision, 2006, ICARCV '06
Country/Territory	Singapore
City	Singapore
Period	5/12/06 → 8/12/06

Keywords

Biometrics
Feature extraction
Manifold learning
Palmprint recognition
Subspace learning

ASJC Scopus subject areas

Computer Science Applications
Computer Vision and Pattern Recognition
Control and Systems Engineering

More information

10.1109/ICARCV.2006.345339

Cite this

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title = "{"}Non-locality{"} preserving projection and its application to palmprint recognition",

abstract = "This paper develops a {"}Non-locality{"} Preserving Projection (NLPP) technique for feature extraction. In contrast to the existing Locality Preserving Projection (LPP), a technique based on the characterization of the local scatter, NLPP is a method based on the characterization of the non-local scatter. Intuitively, NLPP should be more effective than LPP when the non-local information plan a dominant role in discrimination. NLPP is tested using the PolyU palmprint database and the experimental results show that NLPP outperforms PCA, LDA and LPP.",

keywords = "Biometrics, Feature extraction, Manifold learning, Palmprint recognition, Subspace learning",

author = "Jian Yang and Dapeng Zhang and Yang, \{Jing Yu\}",

year = "2006",

month = dec,

day = "1",

doi = "10.1109/ICARCV.2006.345339",

language = "English",

isbn = "1424403421",

booktitle = "9th International Conference on Control, Automation, Robotics and Vision, 2006, ICARCV '06",

note = "9th International Conference on Control, Automation, Robotics and Vision, 2006, ICARCV '06 ; Conference date: 05-12-2006 Through 08-12-2006",

}

Yang, J, Zhang, D & Yang, JY 2006, "Non-locality" preserving projection and its application to palmprint recognition. in 9th International Conference on Control, Automation, Robotics and Vision, 2006, ICARCV '06., 4150180, 9th International Conference on Control, Automation, Robotics and Vision, 2006, ICARCV '06, Singapore, Singapore, 5/12/06. https://doi.org/10.1109/ICARCV.2006.345339

"Non-locality" preserving projection and its application to palmprint recognition. / Yang, Jian; Zhang, Dapeng; Yang, Jing Yu.
9th International Conference on Control, Automation, Robotics and Vision, 2006, ICARCV '06. 2006. 4150180.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

TY - GEN

T1 - "Non-locality" preserving projection and its application to palmprint recognition

AU - Yang, Jian

AU - Zhang, Dapeng

AU - Yang, Jing Yu

PY - 2006/12/1

Y1 - 2006/12/1

N2 - This paper develops a "Non-locality" Preserving Projection (NLPP) technique for feature extraction. In contrast to the existing Locality Preserving Projection (LPP), a technique based on the characterization of the local scatter, NLPP is a method based on the characterization of the non-local scatter. Intuitively, NLPP should be more effective than LPP when the non-local information plan a dominant role in discrimination. NLPP is tested using the PolyU palmprint database and the experimental results show that NLPP outperforms PCA, LDA and LPP.

AB - This paper develops a "Non-locality" Preserving Projection (NLPP) technique for feature extraction. In contrast to the existing Locality Preserving Projection (LPP), a technique based on the characterization of the local scatter, NLPP is a method based on the characterization of the non-local scatter. Intuitively, NLPP should be more effective than LPP when the non-local information plan a dominant role in discrimination. NLPP is tested using the PolyU palmprint database and the experimental results show that NLPP outperforms PCA, LDA and LPP.

KW - Biometrics

KW - Feature extraction

KW - Manifold learning

KW - Palmprint recognition

KW - Subspace learning

UR - https://www.scopus.com/pages/publications/34547183331

U2 - 10.1109/ICARCV.2006.345339

DO - 10.1109/ICARCV.2006.345339

M3 - Conference article published in proceeding or book

SN - 1424403421

SN - 9781424403424

BT - 9th International Conference on Control, Automation, Robotics and Vision, 2006, ICARCV '06

T2 - 9th International Conference on Control, Automation, Robotics and Vision, 2006, ICARCV '06

Y2 - 5 December 2006 through 8 December 2006

ER -

"Non-locality" preserving projection and its application to palmprint recognition

Abstract

Conference

Keywords

ASJC Scopus subject areas

More information

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