Vision-based spoofing face detection using polarised light
Computer vision is an image understanding discipline that studies how to reconstruct, interpret and understand a 3D scene from its 2D images. One of the goals is to automate the analysis of images through the use of computer software and hardware. Meanwhile, biometrics refer to the automated authent...
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| Format: | Thesis Book |
| Language: | English |
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| Summary: | Computer vision is an image understanding discipline that studies how to reconstruct, interpret and understand a 3D scene from its 2D images. One of the goals is to automate the analysis of images through the use of computer software and hardware. Meanwhile, biometrics refer to the automated authentication process that rely on measureable physical characteristics such as individual's unique fingerprints, iris, face, palmprint, gait and voice. Amongst these biometric identification schemes, face biometric is said to be the most popular where face authentication systems have been rapidly developed mainly for security reasons. However, the resistance of face biometric system to spoofing attack, which is an act to impersonate a valid user by placing fake face in front of the sensor to gain access, has become a critical issue. Thus, anti-spoofing technique is required to counter the attacks. Different materials have their own reflection properties. These reflection differences have been manipulated by researches for particular reasons such as in object classification. Many ways can be used to measure the reflection differences of each object. One of them is by using polarised light. Since none of the existing studies applied polarised light in face spoofing detection, therefore in this thesis, polarisation imaging technique was implemented to distinguish between genuine face and two types of spoofing attacks: printed photos and iPad displayed faces. From the investigations, several research findings can be listed. Firstly, unpolarised visible light could not be used in apolarisation imaging system to capture polarised images for designated purpose. Secondly, polarised light is able to differentiate between surface and subsurface reflections of real and fake faces. However, both of these reflections could not be used as one of the classification methods between real face and printed photos. Thirdly, polarised image could contribute to enhance the performance of face recognition system against spoofing attacks in which the newly proposed formula, SDOLP3F achieves higher accuracy rate. Next, near infrared (NIR) light in a polarisation imaging system do not provide significant differences between real face and the two face attacks. Apart from polarised spoofing face detection analysis, experiments to investigate the accuracy of depth data captured by three depth sensors was carried out. This investigation was conducted due to the concerns over the stability of the depth pixels involved in 3D spoofing face reconstruction in a publicly available spoofing face database known as 3DMAD. From the analysis, none of the three depth sensors which are the Kinect for Xbox 360, Kinect for Windows version 2.0 and Asus Xtion Pro Live are suitable for 3D face reconstruction for the purpose of spoofing detection due to the potential errors made by the fluctuated pixels. As a conclusion, polarisation imaging technique has the potential to protect face biometric system from printed photos and iPad displayed attacks. Further investigations using the same polarised light approach could be carried out on other future work as proposed at the end of this thesis. |
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| Physical Description: | xvi, 173 leaves: ill. (some col.); 30cm. |
| Bibliography: | Includes bibliographical references (leaves 163 - 171) |