دانلود مقاله انگلیسی رایگان:یک روش جدید بیومتریک شناختی مبتنی بر الگوی هشت جداره چند هسته ای با استفاده از صدای راه رفتن - 2021
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  • A novel biometric recognition method based on multi kernelled bijection octal pattern using gait sound A novel biometric recognition method based on multi kernelled bijection octal pattern using gait sound
    A novel biometric recognition method based on multi kernelled bijection octal pattern using gait sound

    سال انتشار:

    2021


    عنوان انگلیسی مقاله:

    A novel biometric recognition method based on multi kernelled bijection octal pattern using gait sound


    ترجمه فارسی عنوان مقاله:

    یک روش جدید بیومتریک شناختی مبتنی بر الگوی هشت جداره چند هسته ای با استفاده از صدای راه رفتن


    منبع:

    Sciencedirect - Elsevier - Applied Acoustics, 173 (2021) 107701: doi:10:1016/j:apacoust:2020:107701


    نویسنده:

    Emrah Aydemir


    چکیده انگلیسی:

    Background: Many gait based methods have been presented about biometric identification in the literature. Gait recognition methods have generally used images and sensors signals. In this work, a novel gait based biometric recognition method is presented. A novel Multi Kernelled Bijection Octal Pattern (MK- BOP) is presented in this study. Object: The main aim of the proposed MK-BOP is to extract distinctive and comprehensive features from a signal (gait sound). By using the proposed MK-BOP, a novel biometric recognition method is proposed. Gait sounds are collected, and two novel datasets are collected. The first dataset is a noisy and heterogeneous dataset. The second dataset is a clear and homogenous dataset. A multileveled method is presented to authenticate subjects from these datasets. One dimensional discrete wavelet transform (1D-DWT) is applied to sound signal with Symlet 6 (sym6) filter, and levels are calculated. Conclusion: The proposed MK-BOP generates features from each level signals, and the generated features are concatenated. A hybrid feature selector (RFNCA) selects the most discriminative feature, and selected most discriminative features are forwarded to classifiers. 0.980 and 0.949 success rates were achieved for clear and noisy datasets, respectively.© 2020 Elsevier Ltd. All rights reserved.
    Keywords: Gait recognition | Biometrics | Multi kernelled bijection octal pattern | Information fusion | Sound recognition


    سطح: متوسط
    تعداد صفحات فایل pdf انگلیسی: 9
    حجم فایل: 868 کیلوبایت

    قیمت: رایگان


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