Face Liveness Detection Based on Joint Analysis of RGB and Near-Infrared Image of Faces

Song, Lingxue; Liu, Changsong

doi:10.2352/issn.2470-1173.2018.10.imawm-373

Cited by 13 publications

(5 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Live face recognition is an important part of face recognition, which prevents others from using photos, videos, and face models to complete face recognition in place of the person themselves [15]. In this paper, we use near-infrared face detection to prevent the use of others' photos and videos to help with check-in [16]. According to the optical flow method, the near-infrared face detection uses the time domain change and correlation of the image pixel intensity data to determine the "movement" of the respective pixel position, and then the Gaussian difference filter, LBP feature and support vector machine are used to analyze the running information of each pixel.…”

Section: Face Living Recognitionmentioning

confidence: 99%

Design of Classroom Check-in Algorithm Based on Face Recognition

Song,

Chen

2024

Journal of Big Data and Computing

View full text Add to dashboard Cite

In order to understand the attendance of students in the classroom quickly and accurately, this paper proposes a classroom face recognition check-in algorithm developed based on Python language and OpenCV library. The Video Capture function provided by OpenCV library is used to call the camera for image acquisition, and then the acquired image is preprocessed to realize face detection using Haar-like features, the LBPH algorithm is used to extract features from the face image, and a training model is obtained through feature training and stored in the database. After the check-in is initiated, the acquired images are preprocessed, face detection and feature extraction are performed, and they are compared with the model previously stored in the database. The experimental results show that the algorithm is able to efficiently and accurately realize classroom face recognition check-in while ensuring lower cost.

show abstract

Section: Face Living Recognitionmentioning

confidence: 99%

Design of Classroom Check-in Algorithm Based on Face Recognition

Song,

Chen

2024

Journal of Big Data and Computing

View full text Add to dashboard Cite

show abstract

“…Infrared imaging can be used to counter replay attacks, as the display emits light only at visible wavelengths (i.e. a face does not appear in an infrared picture taken of a display whereas it does appear in an image of an actual person [34]). Another replay-attack-specific surface property is the moiré pattern [35].…”

Section: B) Countermeasures To 2d Attacksmentioning

confidence: 99%

The future of biometrics technology: from face recognition to related applications

Imaoka

Hashimoto

Takahashi

et al. 2021

SIP

View full text Add to dashboard Cite

Biometric recognition technologies have become more important in the modern society due to their convenience with the recent informatization and the dissemination of network services. Among such technologies, face recognition is one of the most convenient and practical because it enables authentication from a distance without requiring any authentication operations manually. As far as we know, face recognition is susceptible to the changes in the appearance of faces due to aging, the surrounding lighting, and posture. There were a number of technical challenges that need to be resolved. Recently, remarkable progress has been made thanks to the advent of deep learning methods. In this position paper, we provide an overview of face recognition technology and introduce its related applications, including face presentation attack detection, gaze estimation, person re-identification and image data mining. We also discuss the research challenges that still need to be addressed and resolved.

show abstract

“…Infrared imaging can be used to counter replay attacks because the display emits light only at visible wavelengths (i.e., a face does not appear in an infrared picture taken of a display whereas it appears in an image of an actual person [17]). Another replayattack-specific surface property is the moiré pattern [18].…”

Section: Countermeasures To 2d Attacksmentioning

confidence: 99%