Face Antispoofing Method Using Color Texture Segmentation on FPGA

Youngjun Moon,Intae Ryoo,Seokhoon Kim,Beijing Chen

doi:10.1155/2021/9939232

Youngjun Moon, Intae Ryoo + Show 2 more

Open Access

https://doi.org/10.1155/2021/9939232

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Abstract

User authentication for accurate biometric systems is becoming necessary in modern real-world applications. Authentication systems based on biometric identifiers such as faces and fingerprints are being applied in a variety of fields in preference over existing password input methods. Face imaging is the most widely used biometric identifier because the registration and authentication process is noncontact and concise. However, it is comparatively easy to acquire face images using SNS, etc., and there is a problem of forgery via photos and videos. To solve this problem, much research on face spoofing detection has been conducted. In this paper, we propose a method for face spoofing detection based on convolution neural networks using the color and texture information of face images. The color-texture information combined with luminance and color difference channels is analyzed using a local binary pattern descriptor. Color-texture information is analyzed using the Cb, S, and V bands in the color spaces. The CASIA-FASD dataset was used to verify the proposed scheme. The proposed scheme showed better performance than state-of-the-art methods developed in previous studies. Considering the AI FPGA board, the performance of existing methods was evaluated and compared with the method proposed herein. Based on these results, it was confirmed that the proposed method can be effectively implemented in edge environments.

Highlights

Authentication systems based on biometric information have been applied to various mobile devices such as smartphones, and many users perform identity authentication using facial or fingerprint information instead of the existing password input methods
We propose a liveness face detection method based on a convolutional neural network utilizing the color and texture information of a face image. e proposed method analyzes the combined color-texture information in terms of its luminance and color difference channels using an LBP descriptor
E receiver operating characteristic (ROC) curves are presented. ese curves show the error of the false positive rates against the true positive rates

Summary

Introduction

Authentication systems based on biometric information have been applied to various mobile devices such as smartphones, and many users perform identity authentication using facial or fingerprint information instead of the existing password input methods. Biometric authentication is being applied to bank transactions and mobile payment applications. Researchers are greatly interested in developing high-performance authentication systems. Face images are very easy to acquire using social networks, etc., and are vulnerable against various spoofing techniques, including printed photos and video replay. To solve this problem, research utilizing software solutions have become popular, rather than antispoofing hardware solutions using additional sensors. Research utilizing software solutions have become popular, rather than antispoofing hardware solutions using additional sensors. ese software approaches can be classified into motion-based methods and texture-based methods [1]

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