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Journal articles on the topic 'Biometrics; Modalities; Face recognition'

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Published: 3 June 2025

Last updated: 31 July 2025

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1

Rohini, B.R., and G. Dr.Thippeswamy. "BIOMETRICS-A PRELIMINARY APPROACH." International Journal of Research - Granthaalayah 5, no. 4 RACSIT (2017): 47–52. https://doi.org/10.5281/zenodo.572294.

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Authentication plays a vital role in Information security. The need for identification of legitimate user has increased in the waking concerns for global security. Biometric recognition Systems is a major tool for Authentication mechanism. Biometrics is the ability to identify and authenticate an individual using one or more of their behavioral or physical characteristics. The Study of Different Biometric Modalities gives a better understanding of Biometric Techniques. We focus our Study on Face Biometrics. This paper emphasizes on better understanding of introduction to Biometrics, Biometric

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B.R., Rohini, and Thippeswamy G. "BIOMETRICS-A PRELIMINARY APPROACH." International Journal of Research -GRANTHAALAYAH 5, no. 4RACSIT (2017): 47–52. http://dx.doi.org/10.29121/granthaalayah.v5.i4racsit.2017.3350.

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Authentication plays a vital role in Information security. The need for identification of legitimate user has increased in the waking concerns for global security. Biometric recognition Systems is a major tool for Authentication mechanism. Biometrics is the ability to identify and authenticate an individual using one or more of their behavioral or physical characteristics. The Study of Different Biometric Modalities gives a better understanding of Biometric Techniques. We focus our Study on Face Biometrics. This paper emphasizes on better understanding of introduction to Biometrics, Biometric

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D S, Dr Dinesh Kumar. "Human Authentication using Face, Voice and Fingerprint Biometrics." International Journal for Research in Applied Science and Engineering Technology 9, no. VII (2021): 853–62. http://dx.doi.org/10.22214/ijraset.2021.36381.

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Multimodal biometric approaches are growing in importance for personal verification and identification, since they provide better recognition results and hence improve security compared to biometrics based on a single modality. In this project, we present a multimodal biometric system that is based on the fusion of face, voice and fingerprint biometrics. For face recognition, we employ Haar Cascade Algorithm, while minutiae extraction is used for fingerprint recognition and we will be having a stored code word for the voice authentication, if any of these two authentication becomes true, the s

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Snehlata, Barde. "Multimodal biometrics system with face, ear, and foot fusion techniques." i-manager’s Journal on Pattern Recognition 10, no. 2 (2023): 27. http://dx.doi.org/10.26634/jpr.10.2.20352.

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Biometrics, as an identification method, is used for various applications, particularly in security technologies. The integration of multiple biometric sources aims to overcome limitations observed in unimodal systems, enhancing recognition accuracy. Fusion techniques, categorized into sensor level, feature level, matching score level, decision level, and rank level, are explored to optimize the combination of information from different modalities. Various fusion schemes, such as feature-level fusion, decision-level fusion, and hybrid systems, are investigated for their effectiveness in integr

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Drosou, A., D. Ioannidis, K. Moustakas, and D. Tzovaras. "Unobtrusive Behavioral and Activity-Related Multimodal Biometrics: The ACTIBIO Authentication Concept." Scientific World JOURNAL 11 (2011): 503–19. http://dx.doi.org/10.1100/tsw.2011.51.

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Unobtrusive Authentication Using ACTIvity-Related and Soft BIOmetrics (ACTIBIO) is an EU Specific Targeted Research Project (STREP) where new types of biometrics are combined with state-of-the-art unobtrusive technologies in order to enhance security in a wide spectrum of applications. The project aims to develop a modular, robust, multimodal biometrics security authentication and monitoring system, which uses a biodynamic physiological profile, unique for each individual, and advancements of the state of the art in unobtrusive behavioral and other biometrics, such as face, gait recognition, a

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Assouma, Abdoul Kamal, Tahirou Djara, and Abdou-Aziz Sobabe. "Multi-Biometrics: Survey and Projection of a New Biometric System." International Journal of Engineering and Advanced Technology 12, no. 3 (2023): 80–87. http://dx.doi.org/10.35940/ijeat.c4008.0212323.

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Multi-biometric systems using feature-level fusion allow more accuracy and reliability in recognition performance than uni-biometric systems. But in practice, this type of fusion is difficult to implement especially when we are facing heterogeneous biometric modalities or incompatible features. The major challenge of feature fusion is to produce a representation of each modality with an excellent level of discrimination. Beyond pure biometric modalities, the use of metadata has proven to improve the performance of biometric systems. In view of these findings, our work focuses on multi-origin b

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Abdoul, Kamal Assouma, Djara Tahirou, and Sobabe Abdou-Aziz. "Multi-Biometrics: Survey and Projection of a New Biometric System." International Journal of Engineering and Advanced Technology (IJEAT) 12, no. 3 (2023): 80–87. https://doi.org/10.35940/ijeat.C4008.0212323.

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<strong>Abstract: </strong>Multi-biometric systems using feature-level fusion allow more accuracy and reliability in recognition performance than uni-biometric systems. But in practice, this type of fusion is difficult to implement especially when we are facing heterogeneous biometric modalities or incompatible features. The major challenge of feature fusion is to produce a representation of each modality with an excellent level of discrimination. Beyond pure biometric modalities, the use of metadata has proven to improve the performance of biometric systems. In view of these findings, our wor

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Singh, Law Kumar, Munish Khanna, and Hitendra Garg. "Multimodal Biometric Based on Fusion of Ridge Features with Minutiae Features and Face Features." International Journal of Information System Modeling and Design 11, no. 1 (2020): 37–57. http://dx.doi.org/10.4018/ijismd.2020010103.

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Multimodal biometrics refers to the exploiting combination of two or more biometric modalities in an identification of a system. Fingerprint, face, retina, iris, hand geometry, DNA, and palm print are physiological traits while voice, signature, keystrokes, gait are behavioural traits used for identification by a system. Single biometric features like faces, fingerprints, irises, retinas, etc., deteriorate or change with time, environment, user mode, physiological defects, and circumstance therefore integrating multi features of biometric traits increase robustness of the system. The proposed

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Ammour, Basma, Larbi Boubchir, Toufik Bouden, and Messaoud Ramdani. "Face–Iris Multimodal Biometric Identification System." Electronics 9, no. 1 (2020): 85. http://dx.doi.org/10.3390/electronics9010085.

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Multimodal biometrics technology has recently gained interest due to its capacity to overcome certain inherent limitations of the single biometric modalities and to improve the overall recognition rate. A common biometric recognition system consists of sensing, feature extraction, and matching modules. The robustness of the system depends much more on the reliability to extract relevant information from the single biometric traits. This paper proposes a new feature extraction technique for a multimodal biometric system using face–iris traits. The iris feature extraction is carried out using an

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Shetkar, Dr. Sharanbasappa, Baswaraj Gadgay, and D. C. Shubhangi. "Advancements in Face Recognition Using Deep Learning Techniques A Comprehensive Review." Journal of Harbin Engineering University 45, no. 3 (2024): 566–71. https://doi.org/10.5281/zenodo.10926464.

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This paper presents a comprehensive overview of recent developments in face recognition using deep learning approaches. We discuss the evolution of deep learning architectures for face recognition, including variations of CNNs such as Siamese networks, triplet loss networks, and attention mechanisms. Furthermore, we explore the challenges and strategies associated with training deep learning models for face recognition tasks, including data augmentation, transfer learning, and domain adaptation. Additionally, we highlight recent advancements in face recognition applica

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Buciu, Ioan, and Alexandru Gacsadi. "Biometrics Systems and Technologies: A survey." International Journal of Computers Communications & Control 11, no. 3 (2016): 315. http://dx.doi.org/10.15837/ijccc.2016.3.2556.

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In a nutshell, a biometric security system requires a user to provide some biometric features which are then verified against some stored biometric templates. Nowadays, the traditional password based authentication method tends to be replaced by advanced biometrics technologies. Biometric based authentication is becoming increasingly appealing and common for most of the human-computer interaction devices. To give only one recent example, Microsoft augmented its brand new Windows 10 OS version with the capability of supporting face recognition when the user login in. This chapter does not inten

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H, C. Shanthakumar, S. Nagaraja G, and Basthikodi Mustafa. "System for Fusion of Face and Speech Modalities Using DTCWT+QFT and MFCC+RASTA Techniques." Indian Journal of Science and Technology 14, no. 42 (2021): 3144–56. https://doi.org/10.17485/IJST/v14i42.1316.

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<strong>Objectives:</strong> The main objective is to propose a multimodal biometric system by forming a fusion of Face and Speech modalities using DTCWT+QFT techniques for face and MFCC+RASTA Techniques for Speech recognitions. The experimental results are compared with existing works and analysed the performance with counterparts. <strong>Methods:</strong> The proposed model, make use of DTCWT and QFT techniques to extract the features of face images and perform fusion of both. The MFCC and RASTA techniques are implemented to extract features of speech data and then fusion is

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Boucetta, Aldjia, and Kamal Eddine Melkemi. "Score Level Fusion of Palmprint, Face and Iris Using Adaptive PSO." International Journal of Applied Metaheuristic Computing 10, no. 3 (2019): 175–94. http://dx.doi.org/10.4018/ijamc.2019070109.

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Systems that use unimodal biometrics often suffer from various drawbacks such as noise in sensed data, variations that are due to intra class, nonuniversality, spoof attacks, restricted degrees of freedom and high error rates. These limitations can be solved effectively by combining two or more biometric modalities. In this article, a multimodal biometric fusion system is presented that combines palmprint, face and iris traits. The biometric fusion is performed at the score level in order to improve the accuracy of the system. Scores obtained from the three classifiers are fused using adaptive

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Shihab A. Shawkat and Raya N. Ismail. "Biometric Technologies in Recognition Systems: A Survey." Tikrit Journal of Pure Science 24, no. 6 (2019): 132–37. http://dx.doi.org/10.25130/tjps.v24i6.449.

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The ability to recognize people uniquely and to associate personal attributes such as name and nationality with them has been very important to the fabric of human society. Nowadays, modern societies have an explosion in population growth and increased mobility which necessitated building advanced identity management systems for recording and maintaining people’s identities. In the last decades, biometrics has played an important role in recognizing people instead of traditional ways such as passwords and keys which can be forgotten or be stolen. Biometric systems employ physiological and/or b

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Shinde, Prashant Pandurang, and Amol Sable. "Hybridization for Classification and Identification of Individuals using Multimodal Biometric Systems." International Journal of Engineering and Advanced Technology (IJEAT) 9, no. 4 (2020): 2126–32. https://doi.org/10.35940/ijeat.D7249.049420.

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Biometric recognition systems use certain human characteristics such as voice, facial features, fingerprint, iris or hand geometry to identify an individual or verify their identity. These systems have been developed individually for each of these biometric modalities until they achieve remarkable levels of performance. Biometrics is a measure of biological characteristics for the identification or authentication of an individual based on some of its characteristics. Although biometric recognition techniques promise to be very effective, At present, we can not guarantee an excellent identifica

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Atenco, Juan Carlos, Juan Carlos Moreno, Juan Manuel Ramirez, Rene Arechiga, Pilar Gomez, and Rigoberto Fonseca. "Bimodal biometric recognition system using Convolutional Neural Networks and fusion of deep audiovisual feature vectors." International Journal of Combinatorial Optimization Problems and Informatics 15, no. 3 (2024): 4–14. http://dx.doi.org/10.61467/2007.1558.2024.v15i2.289.

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In recent years, interest has grown in the use biometric systems for identity authentication tasks in digital services, forensic and security applications. A unimodal system (employing a single biometric trait) with high performance is still vulnerable to falsification attacks such as spoofing. For this reason, research on multimodal biometrics (employing various biometric traits) has increased to reinforce security, increase recognition performance, and make false identity authentication more difficult. In this paper, we propose a bimodal system that combines speech and face modalities by con

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Shawkat1, Shihab A., and Raya N. Ismail2. "Biometric Technologies in Recognition Systems: A Survey." Tikrit Journal of Pure Science 24, no. 6 (2019): 132. http://dx.doi.org/10.25130/j.v24i6.899.

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The ability to recognize people uniquely and to associate personal attributes such as name and nationality with them has been very important to the fabric of human society. Nowadays, modern societies have an explosion in population growth and increased mobility which necessitated building advanced identity management systems for recording and maintaining people’s identities. In the last decades, biometrics has played an important role in recognizing people instead of traditional ways such as passwords and keys which can be forgotten or be stolen. Biometric systems employ physiological and/or b

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C, Sapna Kumari, P. Nagapushpa K, Jayalaxmi H, N. Asha C, S. Harakannanavar Sunil, and S. Jakati Jagadish. "Experimental Analysis of Face and Iris Biometric Traits Based on the Fusion Approach." Indian Journal of Science and Technology 16, no. 31 (2023): 2388–97. https://doi.org/10.17485/IJST/v16i31.314.

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Abstract <strong>Objectives :</strong> To develop an efficient algorithm for face and iris multimodal traits on ORL and CASIA dataset and to increase the performance rate and decrease the error rate of the model. The main goal is to increase the performance rate and decrease the error rate of the model. <strong>Methods:</strong> The proposed algorithm utilizes a fusion of face and iris modalities using Stationary Wavelet Transform (SWT) and Local Binary Pattern (LBP) techniques. The Principal Component Analysis (PCA) is applied to reduce the dimensionality of each sample, improv

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Samihah Abdul Latif, Khairul Azami Sidek, and Aisha Hassan Abdalla Hashim. "An Efficient Iris Recognition Technique using CNN and Vision Transformer." Journal of Advanced Research in Applied Sciences and Engineering Technology 34, no. 2 (2023): 235–45. http://dx.doi.org/10.37934/araset.34.2.235245.

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The usage of biometric identification has increased in recent years, with numerous public and commercial organizations incorporating biometric technologies into their infrastructures. One of the technologies is iris recognition which has been used as a biometric recognition compared to other modalities to combat identity abuse due to its ability to eliminate risk of collisions or false matches even when comparing large populations. The use of CNN is proven to provide high accuracy; however, this technology involves the need for a large dataset and higher computational cost. Therefore, this stu

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Alay, Nada, and Heyam H. Al-Baity. "Deep Learning Approach for Multimodal Biometric Recognition System Based on Fusion of Iris, Face, and Finger Vein Traits." Sensors 20, no. 19 (2020): 5523. http://dx.doi.org/10.3390/s20195523.

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With the increasing demand for information security and security regulations all over the world, biometric recognition technology has been widely used in our everyday life. In this regard, multimodal biometrics technology has gained interest and became popular due to its ability to overcome a number of significant limitations of unimodal biometric systems. In this paper, a new multimodal biometric human identification system is proposed, which is based on a deep learning algorithm for recognizing humans using biometric modalities of iris, face, and finger vein. The structure of the system is b

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Ankur, Jyoti Sarmah, Narayan Dutta Gaurab, Lahkar Dakshee, Lahkar Bimrisha, and Talukdar Neelotpal. "Biometric Authentication- Person Identification using Iris Recognition." International Journal of Innovative Science and Research Technology 7, no. 5 (2022): 1100–1104. https://doi.org/10.5281/zenodo.6658785.

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Biometrics are used to offer person identification by measuring and analyzing people's unique physiological and behavioral characteristics. As demands are increasing on this authentication technique a number of biometric modalities have evolved and used like fingerprint reader, face identifier and iris scanner. The human eye also has features and patterns that are distinctive for recognition. Also, the low-cost equipment for utilizing this technique has made it the most preferable framework in security reasons. As a reliable biometric authentication method, it is considered as the most exp

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Assouma, Abdoul Kamal, Tahirou Djara, Abdou Wahidi Bello, Abdou-Aziz Sobabe, Antoine Vianou, and Wilfried Tomenou. "Face Recognition Using Convolutional Neural Networks and Metadata in a Feature Fusion Model." Current Journal of Applied Science and Technology 42, no. 39 (2023): 38–50. http://dx.doi.org/10.9734/cjast/2023/v42i394256.

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Recent advances in science and technology are raising ever-increasing security issues. In response, traditional authentication systems based on knowledge or possession have been developed, but these soon came up against limitations in terms of security and practicality. To overcome these limitations, other systems based on the individual's unique characteristics, known as biometric modalities, were developed. Of the various ways of improving the performance of biometric systems, feature fusion and the joint use of a pure biometric modality and a soft biometric modality (multi-origin biometrics

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Farmanbar, Mina, and Önsen Toygar. "A Hybrid Approach for Person Identification Using Palmprint and Face Biometrics." International Journal of Pattern Recognition and Artificial Intelligence 29, no. 06 (2015): 1556009. http://dx.doi.org/10.1142/s0218001415560091.

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This paper proposes hybrid approaches based on both feature level and score level fusion strategies to provide a robust recognition system against the distortions of individual modalities. In order to compare the proposed schemes, a virtual multimodal database is formed from FERET face and PolyU palmprint databases. The proposed hybrid systems concatenate features extracted by local and global feature extraction methods such as Local Binary Patterns, Log Gabor, Principal Component Analysis and Linear Discriminant Analysis. Match score level fusion is performed in order to show the effectivenes

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Aruna, Bha. "Medoid Based Model for Face Recognition Using Eigen and Fisher Faces." International Journal of Soft Computing, Mathematics and Control (IJSCMC) 2, no. 3 (2013): 1 to 10. https://doi.org/10.5281/zenodo.3764474.

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Biometric technologies have gained a remarkable impetus in high security applications. Various biometric modalities are widely being used these days. The need for unobtrusive biometric recognition can be fulfilled through Face recognition which is the most natural and non intrusive authentication system. However the vulnerability to changes owing to variations in face due to various factors like pose, illumination, ageing, emotions, expressions etc make it necessary to have robust face recognition systems. Various statistical models have been developed so far with varying degree of accuracy an

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Sudhakar Tiwari. "Biometric Authentication in the Face of Spoofing Threats: Detection and Defense Innovations." Innovative Research Thoughts 9, no. 5 (2023): 402–20. https://doi.org/10.36676/irt.v9.i5.1583.

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Biometric authentication systems have emerged as a critical method of ensuring secure access control across various domains, from mobile phones to financial transactions. However, the systems are increasingly vulnerable to spoofing attacks, where imposter individuals attempt to deceive the biometric sensors using counterfeit biometrics, like images, 3D prints, or printed fingerprints. Spoofing attack development poses a significant threat to the security and reliability of biometric authentication systems. Current defense mechanisms are typically ineffective in providing real-time detection an

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Prof, Hadadi Sudheendra, and N. Krishnamurthy Dr. "Novel Promising Algorithm to suppress Spoof Attack by Cryptography Firewall2014." International Journal of Trend in Scientific Research and Development 2, no. 5 (2018): 102–9. https://doi.org/10.31142/ijtsrd15801.

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Spoof attack suppression by the biometric information incorporation is the new and modern method ofavoid and as well suppression the attack online as well Off line . Wireless networks provide variousadvantages in real world. This can help businesses to increase their productivity, lower cost andeffectiveness, increase scalability and improve relationship with business partners and attractcustomers. In recent decades, we have witnessed the evolution of biometric technology from the firstpioneering works in face and voice recognition to the current state of development wherein a widespectrum of

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Huang, Chi-En, Ching-Chun Chang, and Yung-Hui Li. "Mask Attention-SRGAN for Mobile Sensing Networks." Sensors 21, no. 17 (2021): 5973. http://dx.doi.org/10.3390/s21175973.

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Biometrics has been shown to be an effective solution for the identity recognition problem, and iris recognition, as well as face recognition, are accurate biometric modalities, among others. The higher resolution inside the crucial region reveals details of the physiological characteristics which provides discriminative information to achieve extremely high recognition rate. Due to the growing needs for the IoT device in various applications, the image sensor is gradually integrated in the IoT device to decrease the cost, and low-cost image sensors may be preferable than high-cost ones. Howev

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Upadhyay, Niharika. "Advancements in Face Recognition: From Feature Extraction to Deep Learning Models and Integrated Biometric Solutions." International Journal for Research in Applied Science and Engineering Technology 12, no. 4 (2024): 1509–15. http://dx.doi.org/10.22214/ijraset.2024.63337.

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Abstract: Face recognition is a critical field within computer vision and artificial intelligence, focusing on identifying or verifying individuals through digital images or video frames. This research investigates feature extraction and dimensionality reduction techniques, starting from geometric and appearance-based features to advanced deep learning models like DeepFace and FaceNet. It explores face detection methods such as the Viola-Jones Detector, Histogram of Oriented Gradients (HOG), and Convolutional Neural Networks (CNNs), emphasizing the importance of accurate face detection as a pr

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Bukola, Makinde. "A framework for Modified Firefly Algorithm in Multimodal Biometric Authentication System." International Journal of Engineering and Computer Science 12, no. 07 (2023): 25735–62. http://dx.doi.org/10.18535/ijecs/v12i07.4741.

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Many end users are turning to multimodal biometric systems as a result of the limitations of conventional authentication techniques and unimodal biometric systems for offering a high level of accurate authentication. When high accuracy and security are required, multimodal biometrics are the best choice because to the utilization of numerous identification modalities. It is difficult to identify the best features that contribute to the recognition rate/accuracy and have a high redundancy of features since different features are acquired at the feature level fusion from a variety of physiologic

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Bajaj, Vandana, and Navdeep Kaur. "Popular Physiological Trait Based Biometric Authentication Systems." ECS Transactions 107, no. 1 (2022): 6515–22. http://dx.doi.org/10.1149/10701.6515ecst.

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Biometric systems are mostly preferred by different fields because of their higher security features. In past, passwords were used to identify and validate the genuine users. However, it was not preferred because these can be easily accessed by the third party. Hence, consequently it increases the frequency of fraudulent and breach incidents. In contrast to this, biometric systems provide full authentication of an individual based on their physiological traits and modalities that are used as input to biometric system. The paper presents a review that is mainly focused upon the four physiologic

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Boluma Mangata, Bopatriciat, Trésor Mazambi Kilongo, Pierre Tshibanda wa Tshibanda, Remy Mutapay Tshimona, Jean Pepe Buanga Mapetu, and Eugène Mbuyi Mukendi. "Performance Evaluation of A Three-Modality Biometric System using Multinomial Regression." Journal of Innovation Information Technology and Application (JINITA) 7, no. 1 (2025): 1–18. https://doi.org/10.35970/jinita.v7i1.2287.

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In this article, we explored key concepts related to technology and system efficiency. We have created an innovative biometric system that combines three modalities: fingerprint, facial recognition and voice recognition. This approach guarantees enhanced security and a seamless user experience for access control. We tested our application to obtain the false rejection rate and the false acceptance rate, which gave us the confusion matrix. We then used the multinomial regression method to obtain the various parameter values, which are: FN=0.124, VPP=0.88, Sp=0.88, VPN=0.87, Se=0.87 and F-measur

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Debnath, Saswati, and Pinki Roy. "User Authentication System Based on Speech and Cascade Hybrid Facial Feature." International Journal of Image and Graphics 20, no. 03 (2020): 2050022. http://dx.doi.org/10.1142/s0219467820500229.

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With the increasing demand for security in many fastest growing applications, biometric recognition is the most prominent authentication system. User authentication through speech and face recognition is the important biometric technique to enhance the security. This paper proposes a speech and facial feature-based multi-modal biometric recognition technique to improve the authentication of any system. Mel Frequency Cepstral Coefficients (MFCC) is extracted from audio as speech features. In visual recognition, this paper proposes cascade hybrid facial (visual) feature extraction method based o

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Rahman, Elegbede M., Ismaila W. Oladimeji, Adetunji A. Bola, et al. "Comparative Analysis of Chameleon Swarm Optimization and Weighted Sum Fusion Techniques in Bi-Modal Recognition System." International Journal of Scientific Research and Modern Technology (IJSRMT) 4, no. 1 (2025): 69–76. https://doi.org/10.5281/zenodo.14831325.

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Bi-modal biometric systems integrate modalities such as palm-vein and face by fusion techniques to enhance biometric based security systems. Several techniques (especially evolutionary algorithms/swarm intelligence) have been developed and improvised as fusion techniques to reduce false positive rate and increase accuracies of biometric based recognition systems. However, these new techniques have not been adequately analyzed and compared with the conventional techniques like Weighted Sum rule. This study evaluates the performance of Chameleon Swarm Optimization (swarm intelligence algorithm)

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Han, Qi, Heng Yang, Tengfei Weng, Guorong Chen, Jinyuan Liu, and Yuan Tian. "Multimodal Identification Based on Fingerprint and Face Images via a Hetero-Associative Memory Method." Mathematics 9, no. 22 (2021): 2976. http://dx.doi.org/10.3390/math9222976.

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Multimodal identification, which exploits biometric information from more than one biometric modality, is more secure and reliable than unimodal identification. Face recognition and fingerprint recognition have received a lot of attention in recent years for their unique advantages. However, how to integrate these two modalities and develop an effective multimodal identification system are still challenging problems. Hetero-associative memory (HAM) models store some patterns that can be reliably retrieved from other patterns in a robust way. Therefore, in this paper, face and fingerprint biome

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Bhatti, Kamran Ali, Dr Sajida Parveen, Nadeem Naeem Bhatti, Kamran Ali Larik, and Qurat-ul-ain Soomro. "Fingerprint liveness detection using dynamic local ternary pattern (DLTP)." VFAST Transactions on Software Engineering 12, no. 2 (2024): 123–31. http://dx.doi.org/10.21015/vtse.v12i2.1842.

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Nowadays, biometric confirmation systems are utilized for security applications such as verification and identification. There are various biometric modalities such as fingerprints, face recognition, and iris scans. Biometric systems are superior to PIN and password-based systems because the latter can be easily stolen or forgotten, whereas biometric traits are unique and difficult to replicate or forget. Among biometric modalities, fingerprint recognition is widely employed for security purposes due to the distinctiveness of each individual's fingerprint. However, fingerprint biometric system

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SON, B. "The Fusion of Two User-friendly Biometric Modalities: Iris and Face." IEICE Transactions on Information and Systems E89-D, no. 1 (2006): 372–76. http://dx.doi.org/10.1093/ietisy/e89-d.1.372.

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Shaker, Hala, and Salah Al-Darraji. "Face Anti-Spoofing Detection with Multi-Modal CNN Enhanced by ResNet." Basrah Researches Sciences 50, no. 1 (2024): 12. http://dx.doi.org/10.56714/bjrs.50.1.7.

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The growing prevalence of face recognition technology in various applications, including mobile devices, access control, and financial transactions, highlights its importance. However, the vulnerability of face recognition systems to attacks has been demonstrated, underscoring the necessity of addressing potential weaknesses that attackers may exploit. The paper delves into face presentation attack detection (PAD) within biometric systems, which is crucial for ensuring the reliability and security of face recognition algorithms. To address this issue, the paper proposes a method for face prese

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Sonal, Ajit Singh, and Chander Kant. "Optimized hybrid SVM-RF multi-biometric framework for enhanced authentication using fingerprint, iris, and face recognition." PeerJ Computer Science 11 (February 17, 2025): e2699. https://doi.org/10.7717/peerj-cs.2699.

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This article introduces a hybrid multi-biometric system incorporating fingerprint, face, and iris recognition to enhance individual authentication. The system addresses limitations of uni-modal approaches by combining multiple biometric modalities, exhibiting superior performance and heightened security in practical scenarios, making it more dependable and resilient for real-world applications. The integration of support vector machine (SVM) and random forest (RF) classifiers, along with optimization techniques like bacterial foraging optimization (BFO) and genetic algorithms (GA), improves ef

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Madhuri M. Barhate. "Integrative Fusion Paradigms in Multimodal Biometric Authentication: A High-Precision Framework Leveraging Multi-Trait Synergy for Robust Human Identification." Journal of Information Systems Engineering and Management 10, no. 41s (2025): 544–52. https://doi.org/10.52783/jisem.v10i41s.7963.

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This study presents a robust multimodal biometric recognition system integrating face, ear, iris, and foot traits. Using PCA, Eigen images, Hamming distance, and Haar transforms, trait-specific features were extracted and fused at score, rank, and decision levels. The system was validated on a 100-person self-created dataset, achieving recognition accuracy up to 96%, significantly outperforming unimodal approaches. Score-level fusion with logistic regression reduced the EER to 3.2%, enhancing decision reliability. Practical applications span national ID systems, border control, and secure devi

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Tyagi, Princy, Dr Amit Kumar Bindal, and Deepak Srivastava. "An Optimized Feature-Level Fusion Framework for Multimodal Biometric Authentication Using ML Classifiers." International Journal of Environmental Sciences 11, no. 7s (2025): 120–35. https://doi.org/10.64252/jmz3x190.

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Ensuring secure and accurate identity verification remains a central challenge in biometric authentication systems, particularly when relying on unimodal inputs. This paper proposes a novel hybrid multimodal biometric authentication framework that integrates facial, fingerprint, and iris modalities to enhance performance, security, and robustness. Unlike previous works that rely on isolated biometric traits, the proposed system utilizes a custom-compiled dataset combining two publicly available sources—one for face and iris data and another for fingerprint images—thereby creating a rich, multi

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Saleem, Sehrish, Shahzad Ashraf, and Muhammad K Basit. "CMBA - A CANDID MULTI-PURPOSE BIOMETRIC APPROACH." ICTACT Journal on Image and Video Processing 11, no. 1 (2020): 2211–16. https://doi.org/10.21917/ijivp.2020.0317.

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All humans are born with unique physically identified body characteristics to other persons which remains unchanged throughout life. These characteristics are taken into account by the emerging technology to get recognized from person to person. The technology used by the traditional human identification system sometimes becomes inefficient when data or images received are not up to the acceptable quality mark or when a person has a face covered with mask-like during epidemic virus fistula. In order to overcome the human recognition challenges, a Candid Multi-purpose Biometric Approach (CMBA)

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Snehal, Gondkar* Kurhe Prasad Unde Madhuri. "FACE AND FINGERPRINT PATTERN RETRIEVAL USING UNIQUE CODE." Global Journal of Engineering Science and Research Management 4, no. 4 (2017): 39–45. https://doi.org/10.5281/zenodo.556396.

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The use of number of biometric sources for human recognition is referred to as multibiometrics, which in turn mitigates limitations of single modal biometric systems by increasing identification accuracy, improving the population coverage, and imparting fault-tolerance and improving security. In this paper, we present a method for indexing multiple modality biometric databases which is completely based on index codes .And the index codes are generated by a inbuilt biometric matcher. The indexing mechanism which is executed individually for and the results are then combined together into a fina

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Syed, Zubair Yuneeb Shakeeb Ahmed Tejas B. N. Sneha Singh Dr.C Nandini and Dr. Jahnavi Shankar. "Advanced Secured Key Generation Using User Face and Hand Geometry." INTERNATIONAL JOURNAL OF EMERGING TRENDS IN ENGINEERING AND DEVELOPMENT (IJETED) 15, no. 1 (2025): 52–61. https://doi.org/10.5281/zenodo.15280636.

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<strong>ABSTRACT </strong>        The rapid growth of connected systems has brought significant security concerns, mainly in the field of data protection and user authentication. To address these challenges, this paper presents an innovative security solution combining <strong>Quantum Visual Cryptography</strong> with <strong>Multimodal Biometric Encryption</strong> and <strong>Blockchain Technology</strong>. The system utilizes the advanced cryptographic capabilities of quantum mechanics to enhance data transmission security [1], [6], while incorporating multimod

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Elegbede, M. Rahman, Oladejo Oladapo, W. Oladimeji Ismaila, and Folasade M. Ismaila. "Comparative Analysis of Chameleon Swarm Optimization and Weighted Sum Fusion Techniques in Bi-Modal Recognition System." International Journal of Novel Research in Computer Science and Software Engineering 12, no. 1 (2025): 1–11. https://doi.org/10.5281/zenodo.14604616.

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<strong>Abstract:</strong> Bi-modal biometric systems integrate modalities such as palm-vein and face by fusion techniques to enhance biometric based security systems. Several techniques (especially evolutionary algorithms/swarm intelligence) have been developed and improvised as fusion techniques to reduce false positive rate and increase accuracies of biometric based recognition systems. However, these new techniques have not been adequately analyzed and compared with the conventional techniques like Weighted Sum rule. This study evaluates the performance of Chameleon Swarm Optimization (swa

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Rajiv Ranjan Tewari, Shivangi Srivastav,. "Efficient Approach of Automatic Speech Emotion Recognition (ASR) Using Mutual Information." INFORMATION TECHNOLOGY IN INDUSTRY 9, no. 1 (2021): 595–603. http://dx.doi.org/10.17762/itii.v9i1.177.

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Speech is a significant quality for distinguishing a person in daily human to human interaction/ communication. Like other biometric measures, such as face, iris and fingerprints, voice can therefore be used as a biometric measure for perceiving or identifying the person. Speaker recognition is almost the same as a kind of voice recognition in which the speaker is identified from the expression instead of the message. Automatic Speaker Recognition (ASR) is the way to identify people who rely on highlights that are omitted from speech expressions. Speech signals are awesome correspondence media

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Scheer, Tobias, Markus Rohde, Ralph Breithaupt, Norbert Jung, and Robert Lange. "Customizable Presentation Attack Detection for Improved Resilience of Biometric Applications Using Near-Infrared Skin Detection." Sensors 24, no. 8 (2024): 2389. http://dx.doi.org/10.3390/s24082389.

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Due to their user-friendliness and reliability, biometric systems have taken a central role in everyday digital identity management for all kinds of private, financial and governmental applications with increasing security requirements. A central security aspect of unsupervised biometric authentication systems is the presentation attack detection (PAD) mechanism, which defines the robustness to fake or altered biometric features. Artifacts like photos, artificial fingers, face masks and fake iris contact lenses are a general security threat for all biometric modalities. The Biometric Evaluatio

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Olayiwola, Samseedeen, Olayiwola Ayomide, Oguntoye Ponmile, Awodoye Olayanju, Ganiyu Adesina, and Olusayo Omidiora. "Development of A Palm-Vein Recognition System for Identification and Verification Systems using Enhanced Convolutional Neural Network." FUOYE Journal of Engineering and Technology 9, no. 1 (2024): 62–69. http://dx.doi.org/10.4314/fuoyejet.v9i1.10.

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Biometric authentication systems have gained significant attention in access control applications due to their ability to provide enhanced security and convenience. Among various biometric modalities, palm-vein recognition has emerged as a promising approach, offering high accuracy, reliability, and resistance to forgery. However, existing palm-vein recognition systems often face challenges in implementation costs, computational efficiency, and performance limitations. This research aimed to develop an enhanced palm-vein recognition system for access control applications by optimizing a Convol

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Cauagdan, Keith, and Arvin De La Cruz. "A Literature-Based Evaluation of Cloud-Based Multi- Modal Biometric Authentication for Secure Identity Management in the Philippines." Technologique: A Global Journal on Technological Developments and Scientific Innovations 4, no. 1 (2025): 92–100. https://doi.org/10.62718/vmca.tech-gjtdsi.4.1.sc-0525-021.

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This study performs an integrative review of relevant recent scholarly articles, including peer-reviewed papers, to determine the viability of adopting cloud-based multimodal biometric authentication systems in the Philippines. Based on secondary data extracted from Scopus-indexed and ScienceDirect publications from 2020 to 2024, the study classifies findings concerning performance metrics, data protection mechanisms, and adoption determinants. The evaluation is based on a cloud-secured platform using a mix of biometric modalities such as finger, face, and iris recognition. El_Rahman and Alluh

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Kaur, Mankirat. "Face Facts." Consumer Electronics Test & Development 2023, no. 2 (2023): 24–26. http://dx.doi.org/10.12968/s2754-7744(24)70007-4.

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R., Parimala, and Jayakumar C. "Ear Biometrics- An Alternative Biometric." International Journal of Computer Science and Engineering Communications 1, no. 1 (2013): 54–61. https://doi.org/10.5281/zenodo.821762.

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This paper is one of the parts of a biometric based identity verification security system development project. Today, the most successful biometric based identification technologies such as fingerprint and iris scan are used worldwide in both criminal investigations and high security facilities. Even though Face recognition is one of the developing biometric methods; illumination, makeup, posing, emotional expressions and face-lifting reduce the success of face recognition. A new biometric which is not effected by any of the factors above is needed. The alternative biometric should overcome th

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