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  • Open Access

    ARTICLE

    Novel Multimodal Biometric Feature Extraction for Precise Human Identification

    J. Vasavi1, M. S. Abirami2,*

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1349-1363, 2023, DOI:10.32604/iasc.2023.032604 - 05 January 2023

    Abstract In recent years, biometric sensors are applicable for identifying important individual information and accessing the control using various identifiers by including the characteristics like a fingerprint, palm print, iris recognition, and so on. However, the precise identification of human features is still physically challenging in humans during their lifetime resulting in a variance in their appearance or features. In response to these challenges, a novel Multimodal Biometric Feature Extraction (MBFE) model is proposed to extract the features from the noisy sensor data using a modified Ranking-based Deep Convolution Neural Network (RDCNN). The proposed MBFE model… More >

  • Open Access

    ARTICLE

    A Novel Fusion System Based on Iris and Ear Biometrics for E-exams

    S. A. Shaban*, Hosnia M. M. Ahmed, D. L. Elsheweikh

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3295-3315, 2023, DOI:10.32604/iasc.2023.030237 - 17 August 2022

    Abstract With the rapid spread of the coronavirus epidemic all over the world, educational and other institutions are heading towards digitization. In the era of digitization, identifying educational e-platform users using ear and iris based multimodal biometric systems constitutes an urgent and interesting research topic to preserve enterprise security, particularly with wearing a face mask as a precaution against the new coronavirus epidemic. This study proposes a multimodal system based on ear and iris biometrics at the feature fusion level to identify students in electronic examinations (E-exams) during the COVID-19 pandemic. The proposed system comprises four… More >

  • Open Access

    ARTICLE

    Dynamic Audio-Visual Biometric Fusion for Person Recognition

    Najlaa Hindi Alsaedi*, Emad Sami Jaha

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1283-1311, 2022, DOI:10.32604/cmc.2022.021608 - 03 November 2021

    Abstract Biometric recognition refers to the process of recognizing a person’s identity using physiological or behavioral modalities, such as face, voice, fingerprint, gait, etc. Such biometric modalities are mostly used in recognition tasks separately as in unimodal systems, or jointly with two or more as in multimodal systems. However, multimodal systems can usually enhance the recognition performance over unimodal systems by integrating the biometric data of multiple modalities at different fusion levels. Despite this enhancement, in real-life applications some factors degrade multimodal systems’ performance, such as occlusion, face poses, and noise in voice data. In this… More >

  • Open Access

    ARTICLE

    Real-Time Multimodal Biometric Authentication of Human Using Face Feature Analysis

    Rohit Srivastava1, Ravi Tomar1, Ashutosh Sharma2, Gaurav Dhiman3, Naveen Chilamkurti4, Byung-Gyu Kim5,*

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 1-19, 2021, DOI:10.32604/cmc.2021.015466 - 04 June 2021

    Abstract As multimedia data sharing increases, data security in mobile devices and its mechanism can be seen as critical. Biometrics combines the physiological and behavioral qualities of an individual to validate their character in real-time. Humans incorporate physiological attributes like a fingerprint, face, iris, palm print, finger knuckle print, Deoxyribonucleic Acid (DNA), and behavioral qualities like walk, voice, mark, or keystroke. The main goal of this paper is to design a robust framework for automatic face recognition. Scale Invariant Feature Transform (SIFT) and Speeded-up Robust Features (SURF) are employed for face recognition. Also, we propose a… More >

  • Open Access

    ARTICLE

    Hybrid Multimodal Biometric Template Protection

    Naima Bousnina1, Sanaa Ghouzali2,*, Mounia Mikram1,3, Maryam Lafkih1, Ohoud Nafea4, Muna Al-Razgan2, Wadood Abdul4

    Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 35-51, 2021, DOI:10.32604/iasc.2021.014694 - 07 January 2021

    Abstract Biometric template disclosure starts gaining an important concern in deploying practical biometric authentication systems, where an assailant compromises the database for illegitimate access. To protect biometric templates from disclosure attacks, biometric authentication systems should meet these four requirements: security, diversity, revocability, and performance. Different methods have been suggested in the literature such as feature transformation techniques and biometric cryptosystems. However, no single method could satisfy the four requirements, giving rise to the deployment of hybrid mechanisms. In this context, the current paper proposes a hybrid system for multimodal biometric template protection to provide robustness against… More >

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