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Your search keyword '"Yang, Gongping"' showing total 10 results
Start Over Author "Yang, Gongping" Topic biometrics
10 results on '"Yang, Gongping"'

1. Customized Local Line Binary Pattern Method for Finger Vein Recognition

Author

Liu, Haiying, Song, Lingfei, Yang, Gongping, Yang, Lu, Yin, Yilong, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Zhou, Jie, editor, Wang, Yunhong, editor, Sun, Zhenan, editor, Xu, Yong, editor, Shen, Linlin, editor, Feng, Jianjiang, editor, Shan, Shiguang, editor, Qiao, Yu, editor, Guo, Zhenhua, editor, and Yu, Shiqi, editor

Published
2017
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2. A Survey of Finger Vein Recognition

Author

Yang, Lu, Yang, Gongping, Yin, Yilong, Zhou, Lizhen, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Kobsa, Alfred, Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Sun, Zhenan, editor, Shan, Shiguang, editor, Sang, Haifeng, editor, Zhou, Jie, editor, Wang, Yunhong, editor, and Yuan, Weiqi, editor

Published
2014
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4. Robust ECG biometrics using GNMF and sparse representation.

Author

Li, Rui, Yang, Gongping, Wang, Kuikui, Huang, Yuwen, Yuan, Feng, and Yin, Yilong

Subjects
*ELECTROCARDIOGRAPHY, *MATRIX decomposition, *NONNEGATIVE matrices, *BIOMETRY, *DIMENSION reduction (Statistics), *FEATURE extraction, *VITAL signs
Abstract

• GNMF method is used to integrate the ECG data information, geometry and label information. • GNMF also achieves dimensionality reduction and primary feature extraction. • Sparse representation is utilized to obtain final features to perform ECG matching. • Our method shows robust recognition performance on two public datasets. As a vital sign, Electrocardiogram (ECG) has highly discriminative characteristics in the field of biometrics. This paper aims to propose a novel robust ECG biometric method based on graph regularized non-negative matrix factorization (GNMF) and sparse representation. First, after ECG signal pre-processing and heartbeat segmentation, GNMF is used to reduce the dimensions of each heartbeat. In GNMF, an affinity graph is constructed to encode the geometrical information and label information in order to obtain more discriminative features. Second, in order to seek highly discriminability of ECG, the sparse representation is utilized to perform final feature extraction. We evaluate the method on two public datasets: ECG-ID and MIT-BIH Arrhythmia (MITDB). When fusing three heartbeats as a test sample, the accuracy achieves 98.03% and 100% on the ECG-ID dataset and the MITDB dataset, respectively. Experimental results show that the proposed method is robust for within-session and across-session of the ECG signal. [ABSTRACT FROM AUTHOR]

Published
2020
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5. Learning personalized binary codes for finger vein recognition.

Author

Liu, Haiying, Yang, Gongping, Yang, Lu, and Yin, Yilong

Subjects
*BINARY codes, *FINGERS, *VEINS, *FISHER discriminant analysis, *OBJECT recognition (Computer vision)
Abstract

This paper aims to develop a new local binary learning feature for finger vein images called personalized binary code (PBC). Existing local learning features of the image, such as compact binary face descriptor (CBFD) and discriminant binary descriptor (DBD), ignore the structure of the binary feature corresponding to each class when learning. Inspired by the bit-consistency phenomenon of local binary pattern (LBP), we combine the constraints of within-class sparse constraints with linear discriminant analysis (LDA) criteria in the learning process to explore the bit-consistent structure of learned binary features. Specifically, a multi-directional pixel difference vector is first calculated at each pixel of the training set of finger vein images, and an objective function is designed to learn a discriminative map that projects these multi-directional pixel difference vectors into binary features. Our objective function consists of several constraints: Minimizing quantization error, minimizing within-class variance of learned binary features, and maximizing the between-class variance of learned binary features, and minimizing the L 2,1 norm of the learned features for each class. Next, the algorithm based on alternating direction method (ADM) is designed to solve the optimization problem. Finally, a histogram representation of each finger vein image is constructed by the bag-of-words model. In our experiments, the proposed PBC shows that the leading performance on two public databases in comparison with existing finger vein recognition methods. [ABSTRACT FROM AUTHOR]

Published
2019
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6. A Systematic Review of Finger Vein Recognition Techniques.

Author

Shaheed, Kashif, Liu, Hangang, Yang, Gongping, Qureshi, Imran, Gou, Jie, and Yin, Yilong

Subjects
BIOMETRIC identification, COMPARATIVE studies
Abstract

Biometric identification is the study of physiological and behavioral attributes of an individual to overcome security problems. Finger vein recognition is a biometric technique used to analyze finger vein patterns of persons for proper authentication. This paper presents a detailed review on finger vein recognition algorithms. Such tools include image acquisition, preprocessing, feature extraction and matching methods to extract and analyze object patterns. In addition, we list some novel findings after the critical comparative analysis of the highlighted techniques. The comparative studies indicate that the accuracy of finger vein identification methods is up to the mark. [ABSTRACT FROM AUTHOR]

Published
2018
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7. Identification of People at a Distance Using Effective Block List

Author

Nie, Dongdong, Ma, Qinyong, Hutchison, David, Serieseditor, Kanade, Takeo, Serieseditor, Kittler, Josef, Serieseditor, Kleinberg, Jon M., Serieseditor, Mattern, Friedemann, Serieseditor, Mitchell, John C., Serieseditor, Naor, Moni, Serieseditor, Nierstrasz, Oscar, Serieseditor, Pandu Rangan, C., Serieseditor, Steffen, Bernhard, Serieseditor, Sudan, Madhu, Serieseditor, Terzopoulos, Demetri, Serieseditor, Tygar, Doug, Serieseditor, Vardi, Moshe Y., Serieseditor, Weikum, Gerhard, Serieseditor, Sun, Zhenan, editor, Shan, Shiguan, editor, Yang, Gongping, editor, Zhou, Jie, editor, Wang, Yunhong, editor, and Yin, YiLong, editor

Published
2013
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8. A Novel Iris Image Quality Evaluation Based on Coarse-to-Fine Method

Author

Chen, Ying, Liu, Yuanning, Zhu, Xiaodong, Zhang, Xiaoxu, Xu, Haiying, Huo, Guang, Deng, Ning, Hutchison, David, Serieseditor, Kanade, Takeo, Serieseditor, Kittler, Josef, Serieseditor, Kleinberg, Jon M., Serieseditor, Mattern, Friedemann, Serieseditor, Mitchell, John C., Serieseditor, Naor, Moni, Serieseditor, Nierstrasz, Oscar, Serieseditor, Pandu Rangan, C., Serieseditor, Steffen, Bernhard, Serieseditor, Sudan, Madhu, Serieseditor, Terzopoulos, Demetri, Serieseditor, Tygar, Doug, Serieseditor, Vardi, Moshe Y., Serieseditor, Weikum, Gerhard, Serieseditor, Sun, Zhenan, editor, Shan, Shiguan, editor, Yang, Gongping, editor, Zhou, Jie, editor, Wang, Yunhong, editor, and Yin, YiLong, editor

Published
2013
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9. The CFVD Reflection-Type Finger-Vein Image Database with Evaluation Baseline

Author

Zhang, Congcong, Li, Xiaomei, Liu, Zhi, Zhao, Qijun, Xu, Hui, Su, Fangqi, Hutchison, David, Serieseditor, Kanade, Takeo, Serieseditor, Kittler, Josef, Serieseditor, Kleinberg, Jon M., Serieseditor, Mattern, Friedemann, Serieseditor, Mitchell, John C., Serieseditor, Naor, Moni, Serieseditor, Nierstrasz, Oscar, Serieseditor, Pandu Rangan, C., Serieseditor, Steffen, Bernhard, Serieseditor, Sudan, Madhu, Serieseditor, Terzopoulos, Demetri, Serieseditor, Tygar, Doug, Serieseditor, Vardi, Moshe Y., Serieseditor, Weikum, Gerhard, Serieseditor, Sun, Zhenan, editor, Shan, Shiguan, editor, Yang, Gongping, editor, Zhou, Jie, editor, Wang, Yunhong, editor, and Yin, YiLong, editor

Published
2013
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10. Weight Competitive Coding for Finger-Knuckle-Print Verification

Author

Gao, Guangwei, Yang, Jian, Hutchison, David, Serieseditor, Kanade, Takeo, Serieseditor, Kittler, Josef, Serieseditor, Kleinberg, Jon M., Serieseditor, Mattern, Friedemann, Serieseditor, Mitchell, John C., Serieseditor, Naor, Moni, Serieseditor, Nierstrasz, Oscar, Serieseditor, Pandu Rangan, C., Serieseditor, Steffen, Bernhard, Serieseditor, Sudan, Madhu, Serieseditor, Terzopoulos, Demetri, Serieseditor, Tygar, Doug, Serieseditor, Vardi, Moshe Y., Serieseditor, Weikum, Gerhard, Serieseditor, Sun, Zhenan, editor, Shan, Shiguan, editor, Yang, Gongping, editor, Zhou, Jie, editor, Wang, Yunhong, editor, and Yin, YiLong, editor

Published
2013
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