Titlebook: Handbook of Fingerprint Recognition; Davide Maltoni,Dario Maio,Jianjiang Feng Book 2022Latest edition Springer Nature Switzerland AG 2022

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https://doi.org/10.1007/978-3-030-83624-5Performance; Classification; Fingerprint; Fingerprint Matching; Fingerprint Recognition; Fingerprint Sens

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978-3-030-83626-9Springer Nature Switzerland AG 2022

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箴言

Conducive

Zukunftsmanagement für den Mittelstandons are dedicated to explain the most effective approaches for segmentation, local orientation and frequency extraction, singularity detection and pose estimation, image enhancement, and minutiae and pore detection. The computation of global and local fingerprint image quality is also reviewed. Part

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https://doi.org/10.1007/978-3-658-10783-3clusive classification techniques are first reviewed and their limitations are pointed out. The focus is then shifted to more commonly used indexing methods or multi-stage matching. Details are provided on minutiae-based and deep learning-based indexing approaches. A systematic comparison of existin

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https://doi.org/10.1007/978-3-662-64902-2 fingerprints have been (and still often are) processed semi-automatically; a latent print examiner marks the minutiae in latent prints, followed by an automatic search on an AFIS. This procedure is time-consuming and subjective, which limits both the efficiency and efficacy of identifying the suspe

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Antecedent

https://doi.org/10.1007/978-3-322-90582-6 particularly in forensic applications when a suspect is tried for conviction in a court of law. This has generated interest in designing fingerprint individuality models which will quantify the evidential value of fingerprints. This chapter introduces both theoretical and empirical studies on finge