Cancellable face template algorithm based on speeded-up robust features and winner-takes-all
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Cancellable face template algorithm based on speeded-up robust features and winner-takes-all Hiba Basim Alwan 1
& Ku Ruhana Ku-Mahamud
2
Received: 10 September 2019 / Revised: 9 June 2020 / Accepted: 9 July 2020 # Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract
Features such as face, fingerprint, and iris imprints have been used for authentication in biometric system. The toughest feature amongst these is the face. Extracting a region with the most potential face features from an image for biometric identification followed by illumination enhancement is a commonly used method. However, the region of interest extraction followed by illumination enhancement is sensitive to image face feature displacement, skewed image, and bad illumination. This research presents a cancellable face image algorithm built upon the speeded-up robust features method to extract and select features. A speeded-up robust feature approach is utilised for the image’s features extraction, while Winner-Takes-All hashing is utilised for match-seeking. Finally, the features vectors are projected by utilising a random form of binary orthogonal matrice. Experiments were conducted on Yale and ORL datasets which provide grayscale images of sizes 168 × 192 and 112 × 92 pixels, respectively. The execution of the proposed algorithm was measured against several algorithms using equal error rate metric. It is found that the proposed algorithm produced an acceptable performance which indicates that this algorithm can be used in biometric security applications. Keywords Feature selection. Speeded-up robust feature. Winner-takes-all. Hash function. Cancellable biometric
* Hiba Basim Alwan [email protected] Ku Ruhana Ku-Mahamud [email protected]
1
Ministry of Finance, National Board of Pensions, Centre of Information and Computer Systems, Baghdad, Iraq
2
School of Computing, Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia
Multimedia Tools and Applications
1 Introduction Biometrics is an individual authentication and identification method that utilises many organs. The identification stage implements the verification and validation of users in a dataset while the authentication stage implements acceptance of users [6]. Biometric systems were proposed to mitigate the many challenges that were found in traditional authentication systems. Though many of the problems were solved or mitigated by biometric systems, there remain two major issues of security theft and privacy invasion in current biometric systems. These two problems hinder achieving optimality in biometric systems’ development. This happens due to the magnitude of the security violation involved in biometric identity breach because individual biometric data cannot be changed [10]. Due to the promising nature of biometric authentication systems, substantial adoption has been witnessed in comparison to basic authentication techniques like username-password and token-based methods which are found in different domains of application. However, two key ch
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