Presentation attack detection for face recognition on smartphones: a comprehensive review

Even though the field of Face Presentation Attack Detection (PAD) has been around for quite a long time, but still it is quite a new field to be implemented on smartphones. Implementation on smartphones is different because the limited computing power of the smartphones when compared to computers. P...

Full description

Saved in:
Bibliographic Details
Main Authors: Abdul Ghaffar, Idris, Haji Mohd, Mohd Norzali
Format: Article
Language:English
Published: UTEM 2017
Subjects:
Online Access:http://eprints.uthm.edu.my/4779/1/AJ%202017%20%28633%29.pdf
http://eprints.uthm.edu.my/4779/
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Universiti Tun Hussein Onn Malaysia
Language: English
Description
Summary:Even though the field of Face Presentation Attack Detection (PAD) has been around for quite a long time, but still it is quite a new field to be implemented on smartphones. Implementation on smartphones is different because the limited computing power of the smartphones when compared to computers. Presentation Attack for a face recognition system may happen in various ways, using photograph, video or mask of an authentic user’s face. The Presentation Attack Detection system is vital to counter those kinds of intrusion. Face presentation attack countermeasures are categorized as sensor level or feature level. Face Presentation Attack Detection through the sensor level technique involved in using additional hardware or sensor to protect recognition system from spoofing while feature level techniques are purely software-based algorithms and analysis. Under the feature level techniques, it may be divided into liveness detection; motion analysis; face appearance properties (texture analysis, reflectance); image quality analysis (image distortion); contextual information; challenge response. There are a few types of research have been done for face PAD on smartphones. They also have released the database they used for their testing and performance benchmarking.