Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (68)
  • Open Access

    ARTICLE

    Fusion of Type-2 Neutrosophic Similarity Measure in Signatures Verification Systems: A New Forensic Document Analysis Paradigm

    Shahlaa Mashhadani1,*, Wisal Hashim Abdulsalam1, Oday Ali Hassen2, Saad M. Darwish3

    Intelligent Automation & Soft Computing, Vol.39, No.5, pp. 805-828, 2024, DOI:10.32604/iasc.2024.054611 - 31 October 2024

    Abstract Signature verification involves vague situations in which a signature could resemble many reference samples or might differ because of handwriting variances. By presenting the features and similarity score of signatures from the matching algorithm as fuzzy sets and capturing the degrees of membership, non-membership, and indeterminacy, a neutrosophic engine can significantly contribute to signature verification by addressing the inherent uncertainties and ambiguities present in signatures. But type-1 neutrosophic logic gives these membership functions fixed values, which could not adequately capture the various degrees of uncertainty in the characteristics of signatures. Type-1 neutrosophic representation is also… More >

  • Open Access

    ARTICLE

    DeepBio: A Deep CNN and Bi-LSTM Learning for Person Identification Using Ear Biometrics

    Anshul Mahajan*, Sunil K. Singla

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1623-1649, 2024, DOI:10.32604/cmes.2024.054468 - 27 September 2024

    Abstract The identification of individuals through ear images is a prominent area of study in the biometric sector. Facial recognition systems have faced challenges during the COVID-19 pandemic due to mask-wearing, prompting the exploration of supplementary biometric measures such as ear biometrics. The research proposes a Deep Learning (DL) framework, termed DeepBio, using ear biometrics for human identification. It employs two DL models and five datasets, including IIT Delhi (IITD-I and IITD-II), annotated web images (AWI), mathematical analysis of images (AMI), and EARVN1. Data augmentation techniques such as flipping, translation, and Gaussian noise are applied to More >

  • Open Access

    REVIEW

    Biometric Authentication System on Mobile Environment: A Review

    Qasem Abu Al-Haija1,*, Sara Othman Al-Salameen2

    Computer Systems Science and Engineering, Vol.48, No.4, pp. 897-914, 2024, DOI:10.32604/csse.2024.050846 - 17 July 2024

    Abstract The paper discusses the importance of biometric verification systems in mobile environments and highlights the challenges and strategies used to overcome them in order to ensure the security of mobile devices. Emphasis is placed on evaluating the impact of illumination on the performance of biometric verification techniques and how to address this challenge using image processing techniques. The importance of accurate and reliable data collection to ensure the accuracy of verification processes is also discussed. The paper also highlights the importance of improving biometric verification techniques and directing research toward developing models aimed at reducing More >

  • Open Access

    ARTICLE

    A Hand Features Based Fusion Recognition Network with Enhancing Multi-Modal Correlation

    Wei Wu*, Yuan Zhang, Yunpeng Li, Chuanyang Li, Yan Hao

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 537-555, 2024, DOI:10.32604/cmes.2024.049174 - 16 April 2024

    Abstract Fusing hand-based features in multi-modal biometric recognition enhances anti-spoofing capabilities. Additionally, it leverages inter-modal correlation to enhance recognition performance. Concurrently, the robustness and recognition performance of the system can be enhanced through judiciously leveraging the correlation among multimodal features. Nevertheless, two issues persist in multi-modal feature fusion recognition: Firstly, the enhancement of recognition performance in fusion recognition has not comprehensively considered the inter-modality correlations among distinct modalities. Secondly, during modal fusion, improper weight selection diminishes the salience of crucial modal features, thereby diminishing the overall recognition performance. To address these two issues, we introduce an… More > Graphic Abstract

    A Hand Features Based Fusion Recognition Network with Enhancing Multi-Modal Correlation

  • Open Access

    REVIEW

    A Comprehensive Survey for Privacy-Preserving Biometrics: Recent Approaches, Challenges, and Future Directions

    Shahriar Md Arman1, Tao Yang1,*, Shahadat Shahed2, Alanoud Al Mazroa3, Afraa Attiah4, Linda Mohaisen4

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2087-2110, 2024, DOI:10.32604/cmc.2024.047870 - 27 February 2024

    Abstract The rapid growth of smart technologies and services has intensified the challenges surrounding identity authentication techniques. Biometric credentials are increasingly being used for verification due to their advantages over traditional methods, making it crucial to safeguard the privacy of people’s biometric data in various scenarios. This paper offers an in-depth exploration for privacy-preserving techniques and potential threats to biometric systems. It proposes a noble and thorough taxonomy survey for privacy-preserving techniques, as well as a systematic framework for categorizing the field’s existing literature. We review the state-of-the-art methods and address their advantages and limitations in More >

  • Open Access

    ARTICLE

    Human Gait Recognition for Biometrics Application Based on Deep Learning Fusion Assisted Framework

    Ch Avais Hanif1, Muhammad Ali Mughal1, Muhammad Attique Khan2,3,*, Nouf Abdullah Almujally4, Taerang Kim5, Jae-Hyuk Cha5

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 357-374, 2024, DOI:10.32604/cmc.2023.043061 - 30 January 2024

    Abstract The demand for a non-contact biometric approach for candidate identification has grown over the past ten years. Based on the most important biometric application, human gait analysis is a significant research topic in computer vision. Researchers have paid a lot of attention to gait recognition, specifically the identification of people based on their walking patterns, due to its potential to correctly identify people far away. Gait recognition systems have been used in a variety of applications, including security, medical examinations, identity management, and access control. These systems require a complex combination of technical, operational, and… More >

  • Open Access

    ARTICLE

    Robust Facial Biometric Authentication System Using Pupillary Light Reflex for Liveness Detection of Facial Images

    Puja S. Prasad1, Adepu Sree Lakshmi1, Sandeep Kautish2, Simar Preet Singh3, Rajesh Kumar Shrivastava3, Abdulaziz S. Almazyad4, Hossam M. Zawbaa5, Ali Wagdy Mohamed6,7,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 725-739, 2024, DOI:10.32604/cmes.2023.030640 - 30 December 2023

    Abstract Pupil dynamics are the important characteristics of face spoofing detection. The face recognition system is one of the most used biometrics for authenticating individual identity. The main threats to the facial recognition system are different types of presentation attacks like print attacks, 3D mask attacks, replay attacks, etc. The proposed model uses pupil characteristics for liveness detection during the authentication process. The pupillary light reflex is an involuntary reaction controlling the pupil’s diameter at different light intensities. The proposed framework consists of two-phase methodologies. In the first phase, the pupil’s diameter is calculated by applying… More >

  • Open Access

    ARTICLE

    Fusion of Hash-Based Hard and Soft Biometrics for Enhancing Face Image Database Search and Retrieval

    Ameerah Abdullah Alshahrani*, Emad Sami Jaha, Nahed Alowidi

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3489-3509, 2023, DOI:10.32604/cmc.2023.044490 - 26 December 2023

    Abstract The utilization of digital picture search and retrieval has grown substantially in numerous fields for different purposes during the last decade, owing to the continuing advances in image processing and computer vision approaches. In multiple real-life applications, for example, social media, content-based face picture retrieval is a well-invested technique for large-scale databases, where there is a significant necessity for reliable retrieval capabilities enabling quick search in a vast number of pictures. Humans widely employ faces for recognizing and identifying people. Thus, face recognition through formal or personal pictures is increasingly used in various real-life applications,… More >

  • Open Access

    ARTICLE

    Estimating Anthropometric Soft Biometrics: An Empirical Method

    Bilal Hassan1,*, Hafiz Husnain Raza Sherazi2, Mubashir Ali3, Yusra Siddiqi2

    Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2727-2743, 2023, DOI:10.32604/iasc.2023.039275 - 11 September 2023

    Abstract Following the success of soft biometrics over traditional biometrics, anthropometric soft biometrics are emerging as candidate features for recognition or retrieval using an image/video. Anthropometric soft biometrics uses a quantitative mode of annotation which is a relatively better method for annotation than qualitative annotations adopted by traditional biometrics. However, one of the most challenging tasks is to achieve a higher level of accuracy while estimating anthropometric soft biometrics using an image or video. The level of accuracy is usually affected by several contextual factors such as overlapping body components, an angle from the camera, and… More >

  • Open Access

    ARTICLE

    Fine-Grained Soft Ear Biometrics for Augmenting Human Recognition

    Ghoroub Talal Bostaji*, Emad Sami Jaha

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 1571-1591, 2023, DOI:10.32604/csse.2023.039701 - 28 July 2023

    Abstract Human recognition technology based on biometrics has become a fundamental requirement in all aspects of life due to increased concerns about security and privacy issues. Therefore, biometric systems have emerged as a technology with the capability to identify or authenticate individuals based on their physiological and behavioral characteristics. Among different viable biometric modalities, the human ear structure can offer unique and valuable discriminative characteristics for human recognition systems. In recent years, most existing traditional ear recognition systems have been designed based on computer vision models and have achieved successful results. Nevertheless, such traditional models can… More >

Displaying 1-10 on page 1 of 68. Per Page