Ms. Ying He Profile

Ying He

at Anhui Univ

SPIE Involvement:

Author

Publications (2)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 14 August 2019 Paper

Novel algorithm for finger vein recognition based on inception-resnet module

Xian Wang, Huabin Wang, Ying He, Yijun Ding, Liang Tao

Proceedings Volume 11179, 111791D (2019) https://doi.org/10.1117/12.2539624

Read Abstract +

The finger vein feature extraction algorithm based on global or local features is sensitive to rotation, translation and scaling. Convolutional neural networks have higher robustness, but fewer finger vein samples are prone to over-fitting. Therefore, this paper designs a network architecture FingerveinNet for finger vein recognition. Firstly, based the Inception-resnet^[1] module, the design of the finger vein network architecture is used to extract the multi-scale finger vein features while slowing down the gradient disappearance problem without increasing the parameters. Secondly, the center-loss is used as the loss function to optimize the network model and improve. The discriminability of feature vectors for better detail discrimination. Experiments on three international finger vein databases FV-TJ, FV-USM and PolyU show that the proposed method is robust to rotation and translation, and the effectiveness of the proposed method is verified.

Proceedings Article | 6 May 2019 Paper

Weber local descriptor with edge detection and double Gabor orientations for finger vein recognition

Lulu Ye, Huabin Wang, Mengli Du, Ying He, Liang Tao

Proceedings Volume 11069, 110693J (2019) https://doi.org/10.1117/12.2524211

KEYWORDS: Veins, Feature extraction, Edge detection, Image filtering, Detection and tracking algorithms, Image segmentation, Biometrics

Read Abstract +

Difference summation is utilized to calculate the differential excitation of Weber Local Descriptor (WLD), however, this method is sensitive to noise and may offset positive and negative difference; at the same time, the orientation operator of WLD solely calculates the ratio of the gray difference between the vertical and horizontal orientations, that cannot portray the orientation features of the finger vein effectively. According to the features of finger vein images, this paper based on the differential excitation and orientation operator of Weber descriptors, several improvements are as below: 1)firstly, find the edge area in the image, and optimize the gradient magnitude according to the position of the pixel to increase the discrimination, 2)and then differential excitation is represented by the ratio of the optimized gradient magnitude to the current pixel; 3)double Gabor orientations are leveraged to replace the original gradient orientation to reduce the influence of translation and rotation on recognition; 4)finally, in order to better measure the similarity among features, a cross-matching algorithm is used to improve the recognition rate. In this work, the proposed local descriptor and the cross-matching algorithm are combined for finger vein image recognition, the recognition rates reached 100% and 99. 458% on the two finger vein databases at home and abroad, respectively.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years