Local dual-cross ternary pattern for feature representation

Peng Zhou; Yucong Peng; Jifeng Shen; Baochang Zhang; Wankou Yang

doi:10.1007/978-3-319-46654-5_66

Local dual-cross ternary pattern for feature representation

Peng Zhou
, Yucong Peng
, Jifeng Shen
, Baochang Zhang
, Wankou Yang^*

^*Corresponding author for this work

School of Artificial Intelligence(Institute of Artificial Intelligence)

Southeast University, Nanjing
Key Laboratory of Precision Opto-Mechatronics Technology (Ministry of Education)
Jiangsu University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

Extracting effective features is a fundamental issue in image representation and recognition. In this paper, we present a new feature representation method for image recognition based on Local Ternary Pattern and Dual-Cross Pattern, named Local Dual-Cross Ternary Pattern (LDCTP). LDCTP is a feature representation inspired by the sole textural structure of human faces. It is efficient and only quadruples the cost of computing Local Binary Pattern. Experiments show that LDCTP outperforms other descriptors.

Original language	English
Title of host publication	Biometric Recognition - 11th Chinese Conference, CCBR 2016, Proceedings
Editors	Shiguang Shan, Zhisheng You, Jie Zhou, Weishi Zheng, Yunhong Wang, Zhenan Sun, Jianjiang Feng, Qijun Zhao
Publisher	Springer Verlag
Pages	600-608
Number of pages	9
ISBN (Print)	9783319466538
DOIs	https://doi.org/10.1007/978-3-319-46654-5_66
State	Published - 2016
Event	11th Chinese Conference on Biometric Recognition, CCBR 2016 - Chengdu, China Duration: 14 Oct 2016 → 16 Oct 2016

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9967 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	11th Chinese Conference on Biometric Recognition, CCBR 2016
Country/Territory	China
City	Chengdu
Period	14/10/16 → 16/10/16

Keywords

Face recognition
Feature representation
LBP
LDCTP

Access to Document

10.1007/978-3-319-46654-5_66

Cite this

Zhou, P., Peng, Y., Shen, J., Zhang, B., & Yang, W. (2016). Local dual-cross ternary pattern for feature representation. In S. Shan, Z. You, J. Zhou, W. Zheng, Y. Wang, Z. Sun, J. Feng, & Q. Zhao (Eds.), Biometric Recognition - 11th Chinese Conference, CCBR 2016, Proceedings (pp. 600-608). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9967 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-46654-5_66

Zhou, Peng ; Peng, Yucong ; Shen, Jifeng et al. / Local dual-cross ternary pattern for feature representation. Biometric Recognition - 11th Chinese Conference, CCBR 2016, Proceedings. editor / Shiguang Shan ; Zhisheng You ; Jie Zhou ; Weishi Zheng ; Yunhong Wang ; Zhenan Sun ; Jianjiang Feng ; Qijun Zhao. Springer Verlag, 2016. pp. 600-608 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Local dual-cross ternary pattern for feature representation",

abstract = "Extracting effective features is a fundamental issue in image representation and recognition. In this paper, we present a new feature representation method for image recognition based on Local Ternary Pattern and Dual-Cross Pattern, named Local Dual-Cross Ternary Pattern (LDCTP). LDCTP is a feature representation inspired by the sole textural structure of human faces. It is efficient and only quadruples the cost of computing Local Binary Pattern. Experiments show that LDCTP outperforms other descriptors.",

keywords = "Face recognition, Feature representation, LBP, LDCTP",

author = "Peng Zhou and Yucong Peng and Jifeng Shen and Baochang Zhang and Wankou Yang",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2016.; 11th Chinese Conference on Biometric Recognition, CCBR 2016 ; Conference date: 14-10-2016 Through 16-10-2016",

year = "2016",

doi = "10.1007/978-3-319-46654-5\_66",

language = "英语",

isbn = "9783319466538",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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pages = "600--608",

editor = "Shiguang Shan and Zhisheng You and Jie Zhou and Weishi Zheng and Yunhong Wang and Zhenan Sun and Jianjiang Feng and Qijun Zhao",

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Zhou, P, Peng, Y, Shen, J, Zhang, B & Yang, W 2016, Local dual-cross ternary pattern for feature representation. in S Shan, Z You, J Zhou, W Zheng, Y Wang, Z Sun, J Feng & Q Zhao (eds), Biometric Recognition - 11th Chinese Conference, CCBR 2016, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9967 LNCS, Springer Verlag, pp. 600-608, 11th Chinese Conference on Biometric Recognition, CCBR 2016, Chengdu, China, 14/10/16. https://doi.org/10.1007/978-3-319-46654-5_66

Local dual-cross ternary pattern for feature representation. / Zhou, Peng; Peng, Yucong; Shen, Jifeng et al.
Biometric Recognition - 11th Chinese Conference, CCBR 2016, Proceedings. ed. / Shiguang Shan; Zhisheng You; Jie Zhou; Weishi Zheng; Yunhong Wang; Zhenan Sun; Jianjiang Feng; Qijun Zhao. Springer Verlag, 2016. p. 600-608 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9967 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Local dual-cross ternary pattern for feature representation

AU - Zhou, Peng

AU - Peng, Yucong

AU - Shen, Jifeng

AU - Zhang, Baochang

AU - Yang, Wankou

N1 - Publisher Copyright: © Springer International Publishing AG 2016.

PY - 2016

Y1 - 2016

N2 - Extracting effective features is a fundamental issue in image representation and recognition. In this paper, we present a new feature representation method for image recognition based on Local Ternary Pattern and Dual-Cross Pattern, named Local Dual-Cross Ternary Pattern (LDCTP). LDCTP is a feature representation inspired by the sole textural structure of human faces. It is efficient and only quadruples the cost of computing Local Binary Pattern. Experiments show that LDCTP outperforms other descriptors.

AB - Extracting effective features is a fundamental issue in image representation and recognition. In this paper, we present a new feature representation method for image recognition based on Local Ternary Pattern and Dual-Cross Pattern, named Local Dual-Cross Ternary Pattern (LDCTP). LDCTP is a feature representation inspired by the sole textural structure of human faces. It is efficient and only quadruples the cost of computing Local Binary Pattern. Experiments show that LDCTP outperforms other descriptors.

KW - Face recognition

KW - Feature representation

KW - LBP

KW - LDCTP

UR - https://www.scopus.com/pages/publications/84992451585

U2 - 10.1007/978-3-319-46654-5_66

DO - 10.1007/978-3-319-46654-5_66

M3 - 会议稿件

AN - SCOPUS:84992451585

SN - 9783319466538

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 600

EP - 608

BT - Biometric Recognition - 11th Chinese Conference, CCBR 2016, Proceedings

A2 - Shan, Shiguang

A2 - You, Zhisheng

A2 - Zhou, Jie

A2 - Zheng, Weishi

A2 - Wang, Yunhong

A2 - Sun, Zhenan

A2 - Feng, Jianjiang

A2 - Zhao, Qijun

PB - Springer Verlag

T2 - 11th Chinese Conference on Biometric Recognition, CCBR 2016

Y2 - 14 October 2016 through 16 October 2016

ER -

Zhou P, Peng Y, Shen J, Zhang B, Yang W. Local dual-cross ternary pattern for feature representation. In Shan S, You Z, Zhou J, Zheng W, Wang Y, Sun Z, Feng J, Zhao Q, editors, Biometric Recognition - 11th Chinese Conference, CCBR 2016, Proceedings. Springer Verlag. 2016. p. 600-608. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-46654-5_66

Local dual-cross ternary pattern for feature representation

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