Titlebook: Biometric-Based Physical and Cybersecurity Systems; Mohammad S. Obaidat,Issa Traore,Isaac Woungang Book 2019 Springer Nature Switzerland A

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https://doi.org/10.1007/978-981-99-9742-8verhead while guaranteeing high recognizing accuracy, principal component analysis (PCA) technique is used. Finally, test-bed experiments are conducted to show the performance of ., indicating that . can quickly recognize people in a high accuracy..The chapter starts with the definition of Wi-Fi sig

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https://doi.org/10.1007/978-981-99-9742-8e discuss the key research challenges faced in using stylometry for CA, and we introduce an approach to tackle some of those challenges. Different classification techniques are investigated and evaluated using different public datasets, yielding encouraging performance results.

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https://doi.org/10.1007/978-3-030-93467-5. Hence, this chapter presents a multimodal biometric invariant fusion authentication system based on fusion of Zφ invariant moment of fingerprint and face features. It reduces the storage of more features for authentication and reduces the error rate. The Morlet wavelet transform is used to make th

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https://doi.org/10.1007/978-3-030-93467-5f wearables to capture data from both traditional and new biometric modalities. We present several application scenarios that could exploit biometric authentication techniques using wearables. We review system architectures, including the use of cloud computing to off-load the processing and data st

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https://doi.org/10.1007/978-981-15-5515-2r filters or convex coding, have been discussed. Since image quality plays a significant role, several finger knuckle trait-based image quality parameters have been described. Various finger knuckle ROI enhancement procedures have been highlighted along with multiple feature extraction and matching

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Biometric-Based Physical and Cybersecurity Systems978-3-319-98734-7

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