Journal articles: 'Minuzie biometria'

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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 multimodal biometrics system presents recognition based on face detection and fingerprint physiological traits. This proposed system increases the efficiency, accuracy and decreases execution time of the system as compared to the existing systems. The performance of proposed method is reported in terms of parameters such as False Rejection Rate (FRR), False Acceptance Rate (FAR) and Equal Error Rate (EER) and accuracy is reported at 95.389%.

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Sandhya, Mulagala, and Munaga V. N. K. Prasad. "Cancelable Fingerprint Cryptosystem Using Multiple Spiral Curves and Fuzzy Commitment Scheme." International Journal of Pattern Recognition and Artificial Intelligence 31, no. 04 (2017): 1756004. http://dx.doi.org/10.1142/s0218001417560043.

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The increased use of biometric-based authentication systems in a variety of applications has made biometric template protection an important issue. Unlike conventional systems, biometric cannot be revoked or changed. This made template protection a critical issue to be considered in the recent years. This paper proposes a cancelable fingerprint cryptosystem using multiple spiral curves and fuzzy commitment scheme. The method is built by combining cancelable biometrics and biometric cryptosystems. First, we compute transformed minutiae features using multiple spiral curves. Further, these transformed features are encrypted using fuzzy commitment scheme. Hence, a secure template is obtained. Experimental results and analysis prove the credibility of proposed method with recently presented methods of fingerprint template protection.

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Li, Mengxing, Quan Feng, Jian Zhao, Mei Yang, Lijun Kang, and Lili Wu. "Minutiae Matching with Privacy Protection Based on the Combination of Garbled Circuit and Homomorphic Encryption." Scientific World Journal 2014 (2014): 1–13. http://dx.doi.org/10.1155/2014/525387.

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Biometrics plays an important role in authentication applications since they are strongly linked to holders. With an increasing growth of e-commerce and e-government, one can expect that biometric-based authentication systems are possibly deployed over the open networks in the near future. However, due to its openness, the Internet poses a great challenge to the security and privacy of biometric authentication. Biometric data cannot be revoked, so it is of paramount importance that biometric data should be handled in a secure way. In this paper we present a scheme achieving privacy-preserving fingerprint authentication between two parties, in which fingerprint minutiae matching algorithm is completed in the encrypted domain. To improve the efficiency, we exploit homomorphic encryption as well as garbled circuits to design the protocol. Our goal is to provide protection for the security of template in storage and data privacy of two parties in transaction. The experimental results show that the proposed authentication protocol runs efficiently. Therefore, the protocol can run over open networks and help to alleviate the concerns on security and privacy of biometric applications over the open networks.

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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 system consider the person as authorized person. Fusion at matching score level is then applied to enhance recognition performance. In particular, we employ the product rule in our investigation. The final identification is then performed using a nearest neighbour classifier which is fast and effective. Experimental results confirm that our approach achieves excellent recognition performance, and that the fusion approach outperforms biometric identification based on single modalities.

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Rashid, Mofeed, and Huda Zaki. "RSA Cryptographic Key Generation Using Fingerprint Minutiae." Iraqi Journal for Computers and Informatics 41, no. 1 (2014): 66–69. http://dx.doi.org/10.25195/ijci.v41i1.101.

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Human users find difficult to remember long cryptographic keys. Therefore, researchers, for a long time period, have beeninvestigating ways to use biometric features of the user rather than memorable password or passphrase, in an attempt to produce tough andunrepeatable cryptographic keys and to construct the key unpredictable to a hacker who is deficient of important knowledge about theuser's biometrics. In this paper, generating the strong bio-crypt key based on fingerprint minutiae is presented. At first, the minutiae pointsare extracted from the fingerprint image based on image processing algorithms. Then, the extracted fingerprint minutiae are used forgenerating a 1024 bit prime numbers that used in RSA cypher algorithm to generate 2048 cryptographic key.

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Srivastava, Rohit. "Score-Level Multimodal Biometric Authentication of Humans Using Retina, Fingerprint, and Fingervein." International Journal of Applied Evolutionary Computation 11, no. 3 (2020): 20–30. http://dx.doi.org/10.4018/ijaec.2020070102.

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This paper characterizes a multi-modular framework for confirmation, dependent on the biometric combination of retina, finger vein, and unique mark acknowledgment. The authors have proposed feature extraction in retina acknowledgment model by utilizing SIFT and MINUTIA. Security is the fundamental idea in ATM (Automated Teller Machines) today. The use of multi-modular biometrics can be ATM. The work includes three biometric attributes of a client to be specific retina, unique mark, and finger veins. These are pre-prepared and joined (fused) together for score level combination approach. Retina is chosen as a biometric attribute as there are no parallel retina feature matches except if they are of the comparative client; likewise, retina has a decent vessel design making it a decent confirming methodology when contrasted with other biometric attributes. Security is found in the framework by multi-modular biometric combination of retina with finger vein and unique finger impression. Feature extraction approach and cryptography are utilized so as to accomplish security. The element extraction is finished with the assistance of MINUTIA and SIFT calculation, which are at that point characterized utilizing deep neural network (DNN). The element key focuses are intertwined at score level utilizing separation normal and later matched. The test result assessed utilizing MATLAB delineates the significant improvement in the presentation of multi-modular biometric frameworks with higher qualities in GAR and FAR rates.

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Wang, Feng. "Fusion Fingerprint and Face Multi-Biometrics Recognition Based on D-S Evidence Theory." Advanced Materials Research 459 (January 2012): 644–48. http://dx.doi.org/10.4028/www.scientific.net/amr.459.644.

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Single biometric feature has not meet people's needs. After analyzing fingerprints and face recognition technology, a fused theory is proposed which comprise fingerprints and face multi-biometrics features recognition based on D-S evidence theory. This article first analysis main part of the Face and Fingerprint Identification System, then gives a decision-making on integration in the face and fingerprint recognition method. In this paper we divide minutia features of fingerprint into certain and uncertain region which could make the performance of verification in certain region better than the original performance. By this fusion strategy the whole performance is improved.

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Appati, Justice Kwame, Prince Kofi Nartey, Ebenezer Owusu, and Ismail Wafaa Denwar. "Implementation of a Transform-Minutiae Fusion-Based Model for Fingerprint Recognition." International Journal of Mathematics and Mathematical Sciences 2021 (March 4, 2021): 1–12. http://dx.doi.org/10.1155/2021/5545488.

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Biometrics consists of scientific methods of using a person’s unique physiological or behavioral traits for electronic identification and verification. The traits for biometric identification are fingerprint, voice, face, and palm print recognition. However, this study considers fingerprint recognition for in-person identification since they are distinctive, reliable, and relatively easy to acquire. Despite the many works done, the problem of accuracy still persists which perhaps can be attributed to the varying characteristic of the acquisition devices. This study seeks to improve the issue recognition accuracy with the proposal of the fusion of a two transform and minutiae models. In this study, a transform-minutiae fusion-based model for fingerprint recognition is proposed. The first transform technique, thus wave atom transform, was used for data smoothing while the second transform, thus wavelet, was used for feature extraction. These features were added to the minutiae features for person recognition. Evaluating the proposed design on the FVC 2002 dataset showed a relatively better performance compared to existing methods with an accuracy measure of 100% as to 96.67% and 98.55% of the existing methods.

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Sharma, Uttam, Pradeep Tomar, Syed Sadaf Ali, Neetesh Saxena, and Robin Singh Bhadoria. "Optimized Authentication System with High Security and Privacy." Electronics 10, no. 4 (2021): 458. http://dx.doi.org/10.3390/electronics10040458.

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Authentication and privacy play an important role in the present electronic world. Biometrics and especially fingerprint-based authentication are extremely useful for unlocking doors, mobile phones, etc. Fingerprint biometrics usually store the attributes of the minutia point of a fingerprint directly in the database as a user template. Existing research works have shown that from such insecure user templates, original fingerprints can be constructed. If the database gets compromised, the attacker may construct the fingerprint of a user, which is a serious security and privacy issue. Security of original fingerprints is therefore extremely important. Ali et al. have designed a system for secure fingerprint biometrics; however, their technique has various limitations and is not optimized. In this paper, first we have proposed a secure technique which is highly robust, optimized, and fast. Secondly, unlike most of the fingerprint biometrics apart from the minutiae point location and orientation, we have used the quality of minutiae points as well to construct an optimized template. Third, the template constructed is in 3D shell shape. We have rigorously evaluated the technique on nine different fingerprint databases. The obtained results from the experiments are highly promising and show the effectiveness of the technique.

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Selvarani, P., and N. Malarvizhi. "Multibiometric authentication with MATLAB simulation." International Journal of Engineering & Technology 7, no. 1.7 (2018): 47. http://dx.doi.org/10.14419/ijet.v7i1.7.9389.

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Multimodal Biometric Authentication has been used as more security purpose for establishing the user Identification, Authentication and Verification purpose. Multimodal Biometric like Fingerprint and iris are used in this research work for authentication purpose using Matlab simulation. Fingerprint recognition process like Image Enhancement, binarization, Segmentation, thinning, Minutia marking, and Matching are performed with various techniques like Histogram Equalization, Adaptive Binarization, Morphological operations, Minutiae based techniques etc.,Iris recognition process like Segmentation, Normalization, Encoding and Matching are performed with various techniques like Canny edge detection, Daughman’s Rubber sheet model, Hamming Distance etc., can be applied for Fingerprint and iris recognition for authentication purpose. Finally Performance the measure of Precision, Recall, F-Score and Accuracy has evaluated in both fingerprint and iris. It can be concluded Iris Accuracy is higher 0.96% compared with fingerprint accuracy 0.81%.

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Kour, Jaspreet, M. Hanmandlu, and A. Q. Ansari. "Biometrics in Cyber Security." Defence Science Journal 66, no. 6 (2016): 600. http://dx.doi.org/10.14429/dsj.66.10800.

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Computers play an important role in our daily lives and its usage has grown manifolds today. With ever increasing demand of security regulations all over the world and large number of services provided using the internet in day to day life, the assurance of security associated with such services has become a crucial issue. Biometrics is a key to the future of data/cyber security. This paper presents a biometric recognition system which can be embedded in any system involving access control, e-commerce, online banking, computer login etc. to enhance the security. Fingerprint is an old and mature technology which has been used in this work as biometric trait. In this paper a fingerprint recognition system based on no minutiae features: Fuzzy features and Invariant moment features has been developed. Fingerprint images from FVC2002 are used for experimentation. The images are enhanced for improving the quality and a region of interest (ROI) is cropped around the core point. Two sets of features are extracted from ROI and support vector machine (SVM) is used for verification. An accuracy of 95 per cent is achieved with the invariant moment features using RBF kernel in SVM.

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Jang, Han-Ul, and Heung-Kyu Lee. "Biometric-PKI Authentication System Using Fingerprint Minutiae." Journal of Computer and Communications 02, no. 04 (2014): 25–30. http://dx.doi.org/10.4236/jcc.2014.24004.

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Soetarmono, Anggya N. D. "IDENTIFIKASI SIDIK JARI DENGAN MENGGUNAKAN STRUKTUR MINUTIA." Teknika 1, no. 1 (2012): 36–46. http://dx.doi.org/10.34148/teknika.v1i1.5.

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Penelitian ini membahas tentang sistem identifikasi personal dengan menggunakan kesesuaian biometrik pada pola sidik jari. Sesuai atau tidak sesuainya sebuah sidik jari dapat diketahui setelah melampaui serangkaian proses. Dimulai dari akuisisi citra sidik jari, memperbaiki kualitas citra, kemudian menggali fitur-fitur minutia yang ada pada citra sidik jari, hingga akhirnya dapat diukur nilai kesesuaiannya. Minutiae based matching adalah metode yang dipilih untuk mengukur tingkat kesesuaian pola sidik jari karena metode ini diyakini akan memberikan tingkat akurasi yang lebih baik jika dibandingkan dengan metode pattern based matching yang mana pada metode tersebut hanya membandingkan citra dari dua buah sidik jari.

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Mohamed Khidher, Israa. "Biometric Identification by Fingerprint Image Based Minutiae Detection." JOURNAL OF EDUCATION AND SCIENCE 22, no. 2 (2009): 155–66. http://dx.doi.org/10.33899/edusj.2009.57707.

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Ali, Syed Sadaf, Iyyakutti Iyappan Ganapathi, Surya Prakash, Pooja Consul, and Sajid Mahyo. "Securing biometric user template using modified minutiae attributes." Pattern Recognition Letters 129 (January 2020): 263–70. http://dx.doi.org/10.1016/j.patrec.2019.11.037.

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Jin, Zhe, Andrew Beng Jin Teoh, Bok-Min Goi, and Yong-Haur Tay. "Biometric cryptosystems: A new biometric key binding and its implementation for fingerprint minutiae-based representation." Pattern Recognition 56 (August 2016): 50–62. http://dx.doi.org/10.1016/j.patcog.2016.02.024.

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Nagar, Abhishek, Karthik Nandakumar, and Anil K. Jain. "A hybrid biometric cryptosystem for securing fingerprint minutiae templates." Pattern Recognition Letters 31, no. 8 (2010): 733–41. http://dx.doi.org/10.1016/j.patrec.2009.07.003.

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Vibert, Benoit, Jean-Marie Le Bars, Christophe Charrier, and Christophe Rosenberger. "Logical Attacks and Countermeasures for Fingerprint On-Card-Comparison Systems." Sensors 20, no. 18 (2020): 5410. http://dx.doi.org/10.3390/s20185410.

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Digital fingerprints are being used more and more to secure applications for logical and physical access control. In order to guarantee security and privacy trends, a biometric system is often implemented on a secure element to store the biometric reference template and for the matching with a probe template (on-card-comparison). In order to assess the performance and robustness against attacks of these systems, it is necessary to better understand which information could help an attacker successfully impersonate a legitimate user. The first part of the paper details a new attack based on the use of a priori information (such as the fingerprint classification, sensor type, image resolution or number of minutiae in the biometric reference) that could be exploited by an attacker. In the second part, a new countermeasure against brute force and zero effort attacks based on fingerprint classification given a minutiae template is proposed. These two contributions show how fingerprint classification could have an impact for attacks and countermeasures in embedded biometric systems. Experiments show interesting results on significant fingerprint datasets.

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PRASAD, MUNAGA V. N. K., P. SWATHI, C. R. RAO, and B. L. DEEKSHATULU. "MINIMUM SPANNING TREE (MST) BASED TECHNIQUES FOR GENERATION OF CANCELABLE FINGERPRINT TEMPLATES." International Journal of Pattern Recognition and Artificial Intelligence 28, no. 06 (2014): 1456013. http://dx.doi.org/10.1142/s0218001414560138.

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The biometric community is faced with the difficult problem of protection of the original biometric template. One way of doing this is using a cancelable biometric method, which transforms original biometric template in a noninvertible way and uses the transformed template to verify a person's identity. In this paper, we propose two novel representation methods for fingerprint minutiae. Proposed methods based on this representation are simple to generate cancelable templates without requiring pre-alignment of the fingerprints. The main idea is to generate a minimal spanning tree (MST) for fingerprint minutiae in a three-dimensional (3D) feature space. The chain code representation for a generated MST in a two-dimensional (2D) feature space is proposed. A bit string is then generated by mapping the chain code into 2D array. The fingerprint minutiae based upon the Cartesian system is dealt with in Method-1, while the boundary representation of the minutiae is dealt with in Method-2. The proposed methods are evaluated using FVC2004 and FVC2002 databases and the performance is better compared to existing methods [C. Lee and J. Kim, J. Netw. Comput. Appl.33(3) (2010) 236–246; S. Wang and J. Hu, Pattern Recogn.45 (2012) 4129–4137; S. Wang and J. Hu, Pattern Recogn.47(3) (2014) 1321–1329; Z. Jin, A. B. J. Teoh, T. S. Ong and C. Tee, Expert Syst. Appl.39 (2012) 6157–6167; P. Das, K. Karthik and B. C. Garai, Pattern Recogn.45(9) (2012) 3373–3388; A. B. J. Teoh, D. C. L. Ngo and A. Goh, Pattern Recogn.37(11) (2004) 2245–2255.]

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Jiang, Richard M., and Danny Crookes. "FPGA-based minutia matching for biometric fingerprint image database retrieval." Journal of Real-Time Image Processing 3, no. 3 (2008): 177–82. http://dx.doi.org/10.1007/s11554-008-0079-8.

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Ghouzali, Sanaa, Ohoud Nafea, Abdul Wadood, and Muhammad Hussain. "Cancelable Multimodal Biometrics Based on Chaotic Maps." Applied Sciences 11, no. 18 (2021): 8573. http://dx.doi.org/10.3390/app11188573.

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Biometric authentication systems raise certain concerns with regard to security, violation of privacy, and storage issues of biometric templates. This paper proposes a protection approach of biometric templates storage in a multimodal biometric system while ensuring both the cancelability of biometric templates and the efficiency of the authentication process. We propose applying a chaotic maps-based transform on the biometric features to address the cancelability issue. We used Logistic map and Torus Automorphism to generate cancelable biometric features of the face and fingerprint minutia points, respectively. Both transformed features would be concatenated and saved in the database of the system instead of the original features. In the authentication stage, the similarity scores of both transformed face and fingerprint templates are computed and fused using the weighted sum rule. The results of the experimentation, conducted using images from the ORL face and FVC2002 DB1 fingerprint databases, demonstrated the higher performance of the proposed approach achieving a genuine accept rate equal to 100%. Moreover, the obtained results confirmed the soundness of the proposed cancelable technique to satisfy the biometric systems’ requirements (i.e., security, revocability, and diversity).

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Mon, Ei Ei, Sangsuree Vasupongayya, Montri Karnjanadecha, and Touchai Angchuan. "Evaluating biometrics fingerprint template protection for an emergency situation." Tehnički glasnik 13, no. 4 (2019): 280–85. http://dx.doi.org/10.31803/tg-20191104190328.

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Biometric template protection approaches have been developed to secure the biometric templates against image reconstruction on the stored templates. Two cancellable fingerprint template protection approaches namely minutiae-based bit-string cancellable fingerprint template and modified minutiae-based bit-string cancellable fingerprint template, are selected to be evaluated. Both approaches include the geometric information of the fingerprint into the extracted minutiae. Six modified fingerprint data sets are derived from the original fingerprint images in FVC2002DB1_B and FVC2002DB2_B by conducting the rotation and changing the quality of original fingerprint images according to the environment conditions during an emergency situation such as wet or dry fingers and disoriented angle of fingerprint images. The experimental results show that the modified minutiae-based bit-string cancellable fingerprint template performs well on all conditions during an emergency situation by achieving the matching accuracy between 83% and 100% on FVC2002DB1_B data set and between 99% and 100% on FVC2002DB2_B data set.

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Wang, Lingyu, Graham Leedham, and David Siu-Yeung Cho. "Minutiae feature analysis for infrared hand vein pattern biometrics." Pattern Recognition 41, no. 3 (2008): 920–29. http://dx.doi.org/10.1016/j.patcog.2007.07.012.

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J., Shiny Priyadarshini, and Gladis D. "Analogizing the Thinning Algorithm and Elicitation of Vascular Landmark in Retinal Images." International Journal of Cognitive Informatics and Natural Intelligence 10, no. 3 (2016): 29–37. http://dx.doi.org/10.4018/ijcini.2016070103.

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The retinal tissue is composed of network of blood vessels forming a unique biometric pattern. Feature extraction in retinal blood vessel is becoming an emerging trend in the field of personal identification. Because of its unique identity and less vulnerability to noise and distortion it has become one of the most secured biometric identities. The paper highlights the segmentation of blood vessel and the extraction of feature points such as termination and bifurcation points using Zhang Suen's thinning algorithm in retinal images. A comparison has been made and results are analyzed and tabulated between Zhang Suen and Morphological thinning. The count has been taken for both termination and bifurcation markings as spurious and non- spurious minutiae. The spurious minutiae are removed by using the crossing number method. The results clearly depict that the Zhang Suen's thinning algorithm gives better result when compared to morphological thinning.

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Jadidoleslamy, Hossein. "Designing A Novel Approach for Fingerprint Biometric Detection: Based on Minutiae Extraction." International Journal on Bioinformatics & Biosciences 2, no. 4 (2012): 11–27. http://dx.doi.org/10.5121/ijbb.2012.2402.

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Jagadeesan, A., T. Thillaikkarasi, and Dr K. Duraiswamy. "Cryptographic Key Generation from Multiple Biometric Modalities: Fusing Minutiae with Iris Feature." International Journal of Computer Applications 2, no. 6 (2010): 16–26. http://dx.doi.org/10.5120/673-946.

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Wu, Zhendong, Bin Liang, Lin You, Zhihua Jian, and Jin Li. "High-dimension space projection-based biometric encryption for fingerprint with fuzzy minutia." Soft Computing 20, no. 12 (2015): 4907–18. http://dx.doi.org/10.1007/s00500-015-1778-2.

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Wijaya, Intan Raharni. "Analisis dan Implementasi Metode Gabor Filter dan Support Vector Machine pada Klasifikasi Sidik Jari." Indonesian Journal on Computing (Indo-JC) 2, no. 2 (2017): 37. http://dx.doi.org/10.21108/indojc.2017.2.2.176.

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Pengolahan citra digital semakin diminati, salah satunya pada sistem biometrik. Sistem biometrik merupakan sistem dalam pengenalan berdasarkan pola atau ciri khusus yang dimiliki makhluk hidup terutama manusia. Jenis identifikasi biometrik yang umum digunakan adalah pengenalan sidik jari. Sidik jari banyak digunakan dalam kehidupan sehari-hari selama lebih dari 100 tahun karena penerimaan yang tinggi, permanen, akurat, dan keunikan. Kelebihan sidik jari tersebut disebabkan oleh minutiae yang merupakan garis atau guratan pada sidik jari yang berbeda-beda setiap individu. Klasifikasi sidik jari secara umum terbagi menjadi dua tahap yakni ekstraksi fitur serta klasifikasi fitur. <br /> <br /> Ektraksi fitur dapat dilakukan dengan cara filter seperti gabor filter dengan empat sudut orientasi yang berkisar 0, 45, 90 dan 135 derajat. Hasil dari ekstraksi ciri akan klasifikasi dengan tujutan identifikasi. Metode Support Vector Machine (SVM) dapat digunakan sebagai classifier untuk sistem biometrik sidik jari. SVM memiliki kernel trick yang berpengaruh pada akurasi yang dihasilkan. Digunakan SVM multiclass metode one-against-all dalam klasfikasi sidik jari untuk 25 kelas. Akurasi terbesar diperoleh oleh kernel Radial Basis Function (RBF) sebesar 73% untuk data awal dan 76% untuk penambahan data augmentasi

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MISHRA, KAMTA NATH, PRAKASH C. SRIVASTAVA, ANUPAM AGRAWAL, VIVEK TRIPATHI, and VISHAL GUPTA. "A FRAMEWORK TOWARDS USING EIGEN IRIS, MINUTIAE THUMB AND DNA SEQUENCE FEATURES FOR PERSONAL IDENTIFICATION." International Journal of Information Acquisition 08, no. 03 (2011): 197–225. http://dx.doi.org/10.1142/s0219878911002471.

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Biometric systems based on a single physiological or behavioral characteristic may not be able to identify a person correctly. This paper presents an efficient and reliable multimodal biometric identification system which is based on minutiae thumb, Eigen iris and DNA sequence features. In this method compressed form of Short tandem repeat (STR) part of DNA sequence, compressed thumbprint and compressed iris image (Eigen values) of a person are used for further identification of an individual. Therefore, personal identification including identical twins and dead person's cases will become easier in using this method. Our technique will correctly identify a person (living or dead) on the basis of his thumbprint, iris image and DNA sequence features. We have used thumbprint and iris images for identifying a live person. But, for identifying a dead person we have used STR part of DNA sequence. We tested our method for 100 samples of thumbprints and iris images of CASIA database and we found that our multimodal method is able to correctly identify each and every individual including identical twin on the basis of thumbprints and iris images. For identifying a dead person the compressed form of DNA sequence of that person is used.

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Thangamanimaran, Dhileepan, M. Sharat Chandar, and S. Chandia. "Optimization of biometric recognition using cuckoo search algorithm: a preliminary version for minutia based fingerprint identification." International Journal of Engineering & Technology 7, no. 1.1 (2017): 43. http://dx.doi.org/10.14419/ijet.v7i1.1.8920.

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Currently Behavioural Biometrics is the most widely used means of security. Though Behavioural Biometrics is highly reliable and secure, the data handling process is quite complex. This Problem can be solved by optimizing the process using cuckoo search algorithm.This Paper seeks to optimize the process of fingerprint matching by using an optimal algorithm. The Minutiae in the form of a matrix is extracted from a fingerprint. The Matrix is then split into smaller matrices with increasing dimension and then compared. The matrix with least dimension it is matched. If the Match is true then the verification of next generation bigger matrix is done. If the Match tends to be false then the matrix is skipped and the process is continued for the next matrix in the database. The Process is repeated until accurate match is obtained.Though the time reduced by the optimization of the finger print matching algorithm is insignificant for a smaller data set such as finger print data, it can be a key factor when a larger set of Behavioural biometrics data is considered.

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Rivandi, Pranoko, Astuti Winda, Dewanto Satrio, and Mahmud Iwan Solihin. "Automotive Start–Stop Engine Based on Fingerprint Recognition System." E3S Web of Conferences 130 (2019): 01022. http://dx.doi.org/10.1051/e3sconf/201913001022.

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Automated vehicle security system plays an important rule in nowadays advance automotive technology. One of the methods which can be applied for a security system is based on biometric identification system. Fingerprint recognition is one of the biometric systems that can be applied to the security system. In this work, fingerprint recognition system to start the motorcycle engine is developed. The fingerprint of the owner and other authorized persons will be stored into the database, then while the time of starting the engine of the vehicle, the fingerprint will be validated with the database. The minutiae extraction method is applied to find the difference of fingerprint each other after turn the image into grayscale and thinning. After the extraction, the next step is finding the ridge edge and bifurcation. The result of the image will be used as input to the Artificial Neural Network (ANN) to recognize authorized person only. The experiment of fingerprint recognition system shows that automatic start-stop engine using fingerprint recognition system based minutiae extraction and Artificial Neural Network (ANN) has accuracy 100 % and 100 %, respectively.

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Bercelin, Rose Mary W., N. Subbulakshmi, and Tofflin R. Bini. "Fingerprint Combination of Privacy Preservation is Improved by Delaunay Triangulation Method." Applied Mechanics and Materials 573 (June 2014): 437–41. http://dx.doi.org/10.4028/www.scientific.net/amm.573.437.

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Fingerprints are graphical ridge and valley patterns on the tips of human fingers. Owing to their uniqueness and permanence, the use of fingerprints is considered to be one of the most reliable methods of personal verification. Fingerprints are today among the most popularly used biometric modalities in automatic verification systems. At the same time, Protecting the privacy of Fingerprint is an important one, here a novel system propose protecting fingerprint by combining two different fingerprints. In the enrolment stage, fingerprints will be captured from two different fingers. Minutiae positions are extracted from one fingerprint (its the detailed pattern of the fingerprint). The orientation, (it indicates the flow of ridges and valleys) from other fingerprint, and the reference points are calculated from both the two fingerprints. Extracted combined minutiae templates are stored into database. Here A Delaunay Triangulation indexing scheme has been designed for protecting biometric template and non-invertible template are calculated for verifies the authorized person. By using the Delaunay triangulation method fingerprint privacy has to be improved.

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Fei, Lunke, Shaohua Teng, Jigang Wu, and Imad Rida. "Enhanced Minutiae Extraction for High-Resolution Palmprint Recognition." International Journal of Image and Graphics 17, no. 04 (2017): 1750020. http://dx.doi.org/10.1142/s0219467817500206.

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A palmprint generally possesses about 10 times more minutiae features than a fingerprint, which could provide reliable biometric-based personal authentication. However, wide distribution of various creases in a palmprint creates a number of spurious minutiae. Precisely and efficiently, minutiae extraction is one of the most critical and challenging work for high-resolution palmprint recognition. In this paper, we propose a novel minutiae extraction and matching method for high-resolution palmprint images. The main contributions of this work include the following. First, a circle-boundary consistency is proposed to update the local ridge orientation of some abnormal points. Second, a lengthened Gabor filter is designed to better recover the discontinuous ridges corrupted by wide creases. Third, the principal ridge orientation of palmprint image is calculated to establish an angle alignment system, and coarse-to-fine shifting is performed to obtain the optimal coordinate translation parameters. Following these steps, minutiae matching can be efficiently performed. Experiment results conducted on the public high-resolution palmprint database validate the effectiveness of the proposed method.

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Cherrat, El mehdi, Rachid Alaoui, and Hassane Bouzahir. "A multimodal biometric identification system based on cascade advanced of fingerprint, fingervein and face images." Indonesian Journal of Electrical Engineering and Computer Science 17, no. 3 (2020): 1562. http://dx.doi.org/10.11591/ijeecs.v17.i3.pp1562-1570.

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<p>In this paper, we present a multimodal biometric recognition system that combines fingerprint, fingervein and face images based on cascade advanced and decision level fusion. First, in fingerprint recognition system, the images are enhanced using gabor filter, binarized and passed to thinning method. Then, the minutiae points are extracted to identify that an individual is genuine or impostor. In fingervein recognition system, image processing is required using Linear Regression Line, Canny and local histogram equalization technique to improve better the quality of images. Next, the features are obtained using Histogram of Oriented Gradient (HOG). Moreover, the Convolutional Neural Networks (CNN) and the Local Binary Pattern (LBP) are applied to detect and extract the features of the face images, respectively. In addition, we proposed three different modes in our work. At the first, the person is identified when the recognition system of one single biometric modality is matched. At the second, the fusion is achieved at cascade decision level method based on AND rule when the recognition system of both biometric traits is validated. At the last mode, the fusion is accomplished at decision level method based on AND rule using three types of biometric. The simulation results have demonstrated that the proposed fusion algorithm increases the accuracy to 99,43% than the other system based on unimodal or bimodal characteristics.</p>

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Akila, M., and S. Ravichandran. "Generating Biometric Keys for the Cryptosystem Using the Minutiae Features Present In the Fingerprint." International Journal of Computer Sciences and Engineering 7, no. 5 (2019): 1032–37. http://dx.doi.org/10.26438/ijcse/v7i5.10321037.

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Agung. "Impact of Algorithms for the Extraction of Minutiae Points in Fingerprint Biometrics." Journal of Computer Science 8, no. 9 (2012): 1467–72. http://dx.doi.org/10.3844/jcssp.2012.1467.1472.

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Et. al., Jaichandran R. ,. "Biometric Based User Authentication and Privacy Preserving In Cloud Environment." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 2 (2021): 347–50. http://dx.doi.org/10.17762/turcomat.v12i2.801.

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Cloud technology provides advantage of storage services for individuals and organizations thus making file access easy and simple irrespective of location. The major concern is the security while the file is been outsourced. Maintaining integrity, file unchanged, gaining confidentiality during file outsourced plays an important role. In this paper, we propose identity based data outsourcing technique to provide data security during authorization and storage. For data authorization we propose finger print based authentication. The fingerprint based authentication is performed using Minutae Map algorithm (MM). For data security we convert the data owner files to hash values using SHA algorithm. Finally in the cloud storage stage, data security and data availability is addressed using multiple cloud storage system.

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Kukula, Eric P., Christine R. Blomeke, Shimon K. Modi, and Stephen J. Elliott. "Effect of human-biometric sensor interaction on fingerprint matching performance, image quality and minutiae count." International Journal of Computer Applications in Technology 34, no. 4 (2009): 270. http://dx.doi.org/10.1504/ijcat.2009.024079.

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Singh, Sharad Pratap, Shahanaz Ayub, and J. P. Saini. "Analysis and comparison of normal and altered fingerprint using artificial neural networks." International Journal of Knowledge-based and Intelligent Engineering Systems 25, no. 2 (2021): 243–49. http://dx.doi.org/10.3233/kes-210068.

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Fingerprint matching is based on the number of minute matches between two fingerprints. Implementation mainly includes image enhancement, segmentation, orientation histogram, etc., extraction (completeness) and corresponding minutiae. Finally, a matching score is generated that indicates whether two fingerprints coincide with the help of coding with MATLAB to find the matching score and simulation of Artificial Neural Network extending the feedback of the network. Using the artificial neural network tool, an important advantage is the similarity index between the sample data or unknown data. A neural network is a massively parallel distributed processor consisting of simple processing units that have a natural property to store knowledge and computer experiences are available for use. A fingerprint comparison essentially consists of two fingerprints to generate a fingerprint match score the match score is used to determine whether the two impressions they are of the same finger. The decision is made this study shows the comparison of normal and altered fingerprints using MATLAB coding and data used to study in the self-generated data using biometric scanner also the open source data available on the web is used for finding out matching score or similarity index, The study shows that there is hardly any matching between normal and altered fingerprints of the same person.

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Praseetha, V. M., Saad Bayezeed, and S. Vadivel. "Secure Fingerprint Authentication Using Deep Learning and Minutiae Verification." Journal of Intelligent Systems 29, no. 1 (2019): 1379–87. http://dx.doi.org/10.1515/jisys-2018-0289.

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Abstract Nowadays, there has been an increase in security concerns regarding fingerprint biometrics. This problem arises due to technological advancements in bypassing and hacking methodologies. This has sparked the need for a more secure platform for identification. In this paper, we have used a deep Convolutional Neural Network as a pre-verification filter to filter out bad or malicious fingerprints. As deep learning allows the system to be more accurate at detecting and reducing false identification by training itself again and again with test samples, the proposed method improves the security and accuracy by multiple folds. The implementation of a novel secure fingerprint verification platform that takes the optical image of a fingerprint as input is explained in this paper. The given input is pre-verified using Google’s pre-trained inception model for deep learning applications, and then passed through a minutia-based algorithm for user authentication. Then, the results are compared with existing models.

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Mukhaiyar, Riki. "Generating a Cancellable Fingerprint using Matrices Operations and Its Fingerprint Processing Requirements." Asian Social Science 14, no. 6 (2018): 1. http://dx.doi.org/10.5539/ass.v14n6p1.

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Cancellable fingerprint uses transformed or intentionally distorted biometric data instead of the original biometric data for identifying person. When a set of biometric data is found to be compromised, they can be discarded, and a new set of biometric data can be regenerated. This initial principal is identical with a non-invertible concept in matrices operations. In matrix domain, a matrix cannot be transformed into its original form if it meets several requirements such as non-square form matrix, consist of one zero row/column, and no row as multiple of another row. These conditions can be acquired by implementing three matrix operations using Kronecker Product (KP) operation, Elementary Row Operation (ERO), and Inverse Matrix (INV) operation. KP is useful to produce a non-square form matrix, to enlarge the size of matrix, to distinguish and disguise the element of matrix by multiplying each of elements of the matrix with a particular matrix. ERO can be defined as multiplication and addition force to matrix rows. INV is utilized to transform one matrix to another one with a different element or form as a reciprocal matrix of the original. These three matrix operations should be implemented together in generating the cancellable feature to robust image. So, if once three conditions are met by imposter, it is impossible to find the original image of the fingerprint. The initial aim of these operations is to camouflage the original look of the fingerprint feature into an abstract-look to deceive an un-authorized personal using the fingerprint irresponsibly. In this research, several fingerprint processing steps such as fingerprint pre-processing, core-point identification, region of interest, minutiae extration, etc; are determined to improve the quality of the cancellable feature. Three different databases i.e. FVC2002, FVC2004, and BRC are utilized in this work.

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Kamal, Ahmed, Esam Hagras, and H. A. El-Kamchochi. "Dynamic fractional chaotic biometric isomorphic elliptic curve for partial image encryption." Computer Science and Information Systems 18, no. 3 (2021): 1057–76. http://dx.doi.org/10.2298/csis200502018k.

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In this paper, a Modular Fractional Chaotic Sine Map (MFC-SM) has been introduced to achieve high Lyapunov exponent values and completely chaotic behavior of the bifurcation diagram for high level security. The proposed MFC-SM is compared with the conventional non MFC-SM and it has an excellent chaotic analysis. In addition, the randomness test results indicate that the proposed MFC-SM shows better performance and satisfy all randomness tests. Due to the excellent chaotic properties and good randomization results for the proposed MFC-SM, it is used to be cooperated with the biometric digital identity to achieve dynamic chaotic biometric digital identity. Also, for real time image encryption, both Discrete Wavelet Transform (DWT)partial image encryption and Isomorphic Elliptic Curve (IEC)key exchange are used. In addition, the biometric digital identity is extracted from the user fingerprint image as fingerprint minutia data incorporated with the proposed MFC-SM and hence, a new Dynamic Fractional Chaotic Biometric Digital IdentityIEC (DFC-BID-IEC) has been introduced. Dynamic Fractional Chaotic Key Generator (DFC-KG) is used to control the key schedule for all encryption and decryption processing. The encryption process consists of the confusion and diffusion steps. In the confusion step, the 2D Arnold Cat Map (ACM) is used with secret parameters taken from DFC-KG. Also, the diffusion step is based on the dynamic chaotic self-invertible secret key matrix which can be generated from the proposed MFC-SM. The IEC key exchange secret parameters are generated based on Elliptic Curve Diffie?Hellman(ECDH) key exchange and the isomorphism parametre. Statistical analysis, differential analysis and key sensitivity tests are performed to estimate the security strengths of the proposed DFC-BID-IEC system. The experimental results show that the proposed algorithm is robust against common signal processing attacks and provides a high security level and high speed for image encryption application.

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Jeong, Jae-Won, In-Hoon Jang, and Kwee-Bo Sim. "Fingerprint Matching Algorithm Using String-Based MHC Detector Set." Journal of Advanced Computational Intelligence and Intelligent Informatics 9, no. 2 (2005): 175–80. http://dx.doi.org/10.20965/jaciii.2005.p0175.

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Fingerprints have been widely used in the biometric authentication because of its performance, uniqueness and universality. Lately, the speed of identification has become a very important aspect in the fingerprint-based security applications. Also, the reliability still remains the main issue in the fingerprint identification. A fast and reliable fingerprint matching algorithm based on the process of the "self-nonself" discrimination in the biological immune system was proposed. The proposed algorithm is organized by two-matching stages. The 1st matching stage utilized the self-space and MHC detector string set that are generated from the information of the minutiae and the values of the directional field. The 2nd matching stage was made based on the local-structure of the minutiae. The proposed matching algorithm reduces matching time while maintaining the reliability of the matching algorithm.

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Hakim, Lukman. "Penentuan Tes Kepribadian Calon Mahasiswa Berdasarkan Sidik Jari Menggunakan Minutie dan Support Vector Machine." Journal of Applied Informatics and Computing 4, no. 1 (2020): 28–32. http://dx.doi.org/10.30871/jaic.v4i1.1883.

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Every human being is given its own uniqueness by an almighty god, one of which is a part of the body organs such as the fingerprint pattern of the hand, the fingerprint pattern of each human being determines personality, this can be known from many previous studies, which use fingerprints or someone's detection by the police to capture the perpetrators with the biometry approach in the form of footprint fingerprint records attached to other objects. Determination of a person's personality can be known through fingerprints, and also can adjust prospective students in choosing the study program correctly. Fingerprint student personality identification application provides convenience in determining the choice of prospective students of the study program. The minutie method and the Support Vector Machine algorithm are used in clustering personalities according to training data in the application. The minutie test on the fingerprint pattern shows 100% compatibility, with a precision input image source. SVM algorithm in testing reached 80,9% in grouping personality types accordingly.

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Conti, V., C. Militello, F. Sorbello, and S. Vitabile. "A Multimodal Technique for an Embedded Fingerprint Recognizer in Mobile Payment Systems." Mobile Information Systems 5, no. 2 (2009): 105–24. http://dx.doi.org/10.1155/2009/284124.

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The development and the diffusion of distributed systems, directly connected to recent communication technologies, move people towards the era of mobile and ubiquitous systems. Distributed systems make merchant-customer relationships closer and more flexible, using reliable e-commerce technologies. These systems and environments need many distributed access points, for the creation and management of secure identities and for the secure recognition of users. Traditionally, these access points can be made possible by a software system with a main central server. This work proposes the study and implementation of a multimodal technique, based on biometric information, for identity management and personal ubiquitous authentication. The multimodal technique uses both fingerprint micro features (minutiae) and fingerprint macro features (singularity points) for robust user authentication. To strengthen the security level of electronic payment systems, an embedded hardware prototype has been also created: acting as self-contained sensors, it performs the entire authentication process on the same device, so that all critical information (e.g. biometric data, account transactions and cryptographic keys), are managed and stored inside the sensor, without any data transmission. The sensor has been prototyped using the Celoxica RC203E board, achieving fast execution time, low working frequency, and good recognition performance.

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Selvarani, P., and N. Malarvizhi. "Secure data in cloud with multimodal key generation." International Journal of Engineering & Technology 7, no. 1.7 (2018): 27. http://dx.doi.org/10.14419/ijet.v7i1.7.9382.

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Data Security is the Major problem in Cloud Computing. In order to overcome the data security problem the proposed technique utilizes effective data storage using biometric-based cryptographic authentication to support the user authentication for the cloud environment. For user authentication here we are considering iris and fingerprint. Initially the feature values are extracted from the iris and fingerprint using local binary pattern and Minutiae extraction respectively. Local binary pattern operator works with the eight neighbors of a pixel, using the value of this center pixel as a threshold. Minutiae points are the major features of a fingerprint image and are used in the matching of fingerprints. These minutiae points are used to determine the uniqueness of a fingerprint image. Based on that the proposed feature values are extracted from the iris and fingerprint image. In order to improve the security, the suggested technique utilizes the optimal features. For selecting the optimal features hybrid particle swarm optimization and genetic algorithm (HPSOGA) is utilized. Particle swarm optimization (PSO) is a population based stochastic optimization technique. The system is initialized with a population of random solutions and searches for optima by updating generations. In PSO, the potential solutions, called particles, fly through the problem space by following the current optimum particles. Genetic Algorithms (GAs) are adaptive heuristic search algorithm based on the evolutionary ideas of natural selection and genetics. In our proposed method these two optimization algorithm is hybrid for more secure. From the optimization algorithm the suggested technique selects the optimal features. and then the optimal features are used to encrypt the input data. For encryption and decryption, the proposed technique utilizes Triple DES algorithm. Finally the encrypted data is stored in cloud. The performance of the proposed technique is evaluated in terms of encryption and decryption time, memory utilization and overall execution time. Our proposed data storage using biometric-based authentication is implemented with the help of Cloud simulator in the working platform of java.

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Rakib, Nibras Ar, SM Zamshed Farhan, Md Mashrur Bari Sobhan, Jia Uddin, and Arafat Habib. "A Novel 2D Feature Extraction Method for Fingerprints Using Minutiae Points and Their Intersections." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 5 (2017): 2547. http://dx.doi.org/10.11591/ijece.v7i5.pp2547-2554.

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The field of biometrics has evolved tremendously for over the last century. Yet scientists are still continuing to come up with precise and efficient algorithms to facilitate automatic fingerprint recognition systems. Like other applications, an efficient feature extraction method plays an important role in fingerprint based recognition systems. This paper proposes a novel feature extraction method using minutiae points of a fingerprint image and their intersections. In this method, initially, it calculates the ridge ends and ridge bifurcations of each fingerprint image. And then, it estimates the minutiae points for the intersection of each ridge end and ridge bifurcation. In the experimental evaluation, we tested the extracted features of our proposed model using a support vector machine (SVM) classifier and experimental results show that the proposed method can accurately classify different fingerprint images.

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Yaacob, Roszaharah, Chok Dong Ooi, Haidi Ibrahim, Nik Fakhuruddin Nik Hassan, Puwira Jaya Othman, and Helmi Hadi. "Automatic Extraction of Two Regions of Creases from Palmprint Images for Biometric Identification." Journal of Sensors 2019 (January 22, 2019): 1–12. http://dx.doi.org/10.1155/2019/5128062.

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Palmprint has become one of the biometric modalities that can be used for personal identification. This modality contains critical identification features such as minutiae, ridges, wrinkles, and creases. In this research, feature from creases will be our focus. Feature from creases is a special salient feature of palmprint. It is worth noting that currently, the creases-based identification is still not common. In this research, we proposed a method to extract crease features from two regions. The first region of interest (ROI) is in the hypothenar region, whereas another ROI is in the interdigital region. To speed up the extraction, most of the processes involved are based on the processing of the image that has been a downsampled image by using a factor of 10. The method involved segmentations through thresholding, morphological operations, and the usage of the Hough line transform. Based on 101 palmprint input images, experimental results show that the proposed method successfully extracts the ROIs from both regions. The method has achieved an average sensitivity, specificity, and accuracy of 0.8159, 0.9975, and 0.9951, respectively.

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Byeon, Yeong-Hyeon, and Keun-Chang Kwak. "Pre-Configured Deep Convolutional Neural Networks with Various Time-Frequency Representations for Biometrics from ECG Signals." Applied Sciences 9, no. 22 (2019): 4810. http://dx.doi.org/10.3390/app9224810.

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We evaluated electrocardiogram (ECG) biometrics using pre-configured models of convolutional neural networks (CNNs) with various time-frequency representations. Biometrics technology records a person’s physical or behavioral characteristics in a digital signal via a sensor and analyzes it to identify the person. An ECG signal is obtained by detecting and amplifying a minute electrical signal flowing on the skin using a noninvasive electrode when the heart muscle depolarizes at each heartbeat. In biometrics, the ECG is especially advantageous in security applications because the heart is located within the body and moves while the subject is alive. However, a few body states generate noisy biometrics. The analysis of signals in the frequency domain has a robust effect on the noise. As the ECG is noise-sensitive, various studies have applied time-frequency transformations that are robust to noise, with CNNs achieving a good performance in image classification. Studies have applied time-frequency representations of the 1D ECG signals to 2D CNNs using transforms like MFCC (mel frequency cepstrum coefficient), spectrogram, log spectrogram, mel spectrogram, and scalogram. CNNs have various pre-configured models such as VGGNet, GoogLeNet, ResNet, and DenseNet. Combinations of the time-frequency representations and pre-configured CNN models have not been investigated. In this study, we employed the PTB (Physikalisch-Technische Bundesanstalt)-ECG and CU (Chosun University)-ECG databases. The MFCC accuracies were 0.45%, 2.60%, 3.90%, and 0.25% higher than the spectrogram, log spectrogram, mel spectrogram, and scalogram accuracies, respectively. The Xception accuracies were 3.91%, 0.84%, and 1.14% higher than the VGGNet-19, ResNet-101, and DenseNet-201 accuracies, respectively.

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SRIHARI, SARGUR N., and HARISH SRINIVASAN. "COMPARISON OF ROC AND LIKELIHOOD DECISION METHODS IN AUTOMATIC FINGERPRINT VERIFICATION." International Journal of Pattern Recognition and Artificial Intelligence 22, no. 03 (2008): 535–53. http://dx.doi.org/10.1142/s0218001408006326.

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The biometric verification task is to determine whether or not an input and a template belong to the same individual. In the context of automatic fingerprint verification the task consists of three steps: feature extraction, where features (typically minutiae) are extracted from each fingerprint, scoring, where the degree of match between the two sets of features is determined, and decision, where the score is used to accept or reject the hypothesis that the input and template belong to the same individual. The paper focuses on the final decision step, which is a binary classification problem involving a single score variable. The commonly used decision method is to learn a score threshold from a labeled set of inputs and templates, by first determining the receiver operating characteristic (ROC) of the task. The ROC method works well when there is a well-registered fingerprint image. The paper shows that when there is uncertainty due to fingerprint quality, e.g. the input is a latent print or a partial print, the decision method can be improved by using the likelihood ratio of match/non match. The likelihood ratio is obtained by modeling the distributions of same finger and different finger scores using parametric distributions. The parametric forms considered are Gaussian and Gamma distributions whose parameters are learnt from labeled training samples. The performances of the likelihood and ROC methods are compared for varying numbers of minutiae points available for verification. Using either Gaussian or Gamma parametric distributions, the likelihood method has a lower error rate than the ROC method when few minutiae points are available. Likelihood and ROC methods converge to the same accuracy as more minutiae points are available.

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Journal articles on the topic 'Minuzie biometria'

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