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Artykuły w czasopismach na temat „FingerPrint Detection”

Autor: Grafiati

Data publikacji: 3 czerwca 2025

Data aktualizacji: 31 lipca 2025

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Yogita, Verma* Prof. Bhagwati Charan Patel. "FINGERPRINT DETECTION AND RECOGNIZATION TECHNIQUES USING GABOR FILTER." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 6, no. 5 (2017): 722–29. https://doi.org/10.5281/zenodo.801293.

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Fingerprints are most extensively and effectively appropriate for the proof of identity in present days. Mostly because of their uniqueness among the people, public acceptance, originality, stability through life, and their least risk of invasion. Fingerprint technology, which is basically a biometric system, is utilized to identify an individual based on their physical qualities. Fingerprint matching is the trendiest biometric method appropriate to provide authentication. Fingerprint verification is one of the most trustable biometric security system in the world of computers. In this paper w

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Chavan, Vilas A., Devidas S. Bhagat, and Ajit K. Gangawane. "Overview of bimetallic nanomaterials used for visualization of latent fingerprints on various surfaces." Problems of Forensic Sciences, no. 129 (September 8, 2022): 75–91. http://dx.doi.org/10.4467/12307483pfs.22.004.16305.

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This review focuses on the current trends in the use of doped metallic nanomaterials in forensic science for the development and detection of latent fingerprints (LFPs) on various surfaces which provide better fingerprint image quality. The advantages and important results of studies conducted on latent fingerprints detection with various doped metallic nanomaterials are critically discussed. We also glimpse on fluorescent nanoparticles that have succeeded in producing high-quality fingerprint images which lead to the extraction of all three levels of fingerprint features. A few metallic nanom

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Latha, K., and C. Manikandan. "Critical Analysis and Detection of Altered Fingerprints Using Evolutionary Computation Algorithm." Applied Mechanics and Materials 573 (June 2014): 483–88. http://dx.doi.org/10.4028/www.scientific.net/amm.573.483.

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The widespread operation of modified algorithm (National Institution of Standard Technology Fingerprint image Quality (NIFQ)) in government applications allow some persons with illegal environment by neglecting the detection of altered fingerprints. By using the fingerprint quality assessment software, it is difficult to find the altered fingerprints, since the quality of image does not degrade. This paper focuses on optimizing the modified NFIQ algorithm by implementing particle swarm optimization (PSO) based on a fingerprint identification system. It can also be helpful in improving the perf

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Mohammed, Fatima, and Samira A. Mahdi. "Detection Measurements of Some Drugs Materials in Fingerprints." NeuroQuantology 20, no. 5 (2022): 483–87. http://dx.doi.org/10.14704/nq.2022.20.5.nq22198.

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The major goal of this project is to use the Gas Chromatography–Mass Spectrometry (GC-MS) instrument to evaluate the fingerprints of illicit amphetamine. Samples of amphetamine were obtained from the Iraqi Narcotics Control Bureau. The fingerprints were examined before and after contamination with anesthetic powder. The results showed a clear difference between the spectrum of the pure fingerprint and the spectrum of the contaminated fingerprint with amphetamine. The highest peak of the drug sample was recorded at the time (6.80) minutes and Abundance 120000, and in contrast the appearance of

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Lee, Youn Kyu, Jongwook Jeong, and Dongwoo Kang. "An Effective Orchestration for Fingerprint Presentation Attack Detection." Electronics 11, no. 16 (2022): 2515. http://dx.doi.org/10.3390/electronics11162515.

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Fingerprint presentation attack detection has become significant due to a wide-spread usage of fingerprint authentication systems. Well-replicated fingerprints easily spoof the authentication systems because their captured images do not differ from those of genuine fingerprints in general. While a number of techniques have focused on fingerprint presentation attack detection, they suffer from inaccuracy in determining the liveness of fingerprints and performance degradation on unknown types of fingerprints. To address existing limitations, we present a robust fingerprint presentation attack de

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Jiang, Yujia, and Xin Liu. "Uniform Local Binary Pattern for Fingerprint Liveness Detection in the Gaussian Pyramid." Journal of Electrical and Computer Engineering 2018 (2018): 1–9. http://dx.doi.org/10.1155/2018/1539298.

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Fingerprint recognition schemas are widely used in our daily life, such as Door Security, Identification, and Phone Verification. However, the existing problem is that fingerprint recognition systems are easily tricked by fake fingerprints for collaboration. Therefore, designing a fingerprint liveness detection module in fingerprint recognition systems is necessary. To solve the above problem and discriminate true fingerprint from fake ones, a novel software-based liveness detection approach using uniform local binary pattern (ULBP) in spatial pyramid is applied to recognize fingerprint livene

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Menzel, E. Roland. "Recent Advances in Photoluminescence Detection of Fingerprints." Scientific World JOURNAL 1 (2001): 498–509. http://dx.doi.org/10.1100/tsw.2001.76.

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Photoluminescence detection of latent fingerprints has over the last quarter century brought about a new level of fingerprint detection sensitivity. The current state of the art is briefly reviewed to set the stage for upcoming new fingerprint processing strategies. These are designed for suppression of background fluorescence from articles holding latent prints, an often serious problem. The suppression of the background involves time-resolved imaging, which is dealt with from the perspective of instrumentation as well as the design of fingerprint treatment strategies. These focus on lanthani

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Almehmadi, Abdulaziz. "A Behavioral-Based Fingerprint Liveness and Willingness Detection System." Applied Sciences 12, no. 22 (2022): 11460. http://dx.doi.org/10.3390/app122211460.

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Fingerprints have been used for decades to verify the identity of an individual for various security reasons. Attackers have developed many approaches to deceive a fingerprint verification system, ranging from the sensor level, where gummy fingers are created, to gaining access to the decision-maker level, where the decision is made based on low matching criteria. Even though fingerprint sensor-level countermeasures have developed advanced metrics to detect any attempt to dupe the system, attackers still manage to outwit a fingerprint verification system. In this paper, we present the Micro-be

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Madhav, Yagnasri, Dr S. China Venkateshwarlu, and Dr V. Siva Nagaraju. "Advanced Fingerprint Alteration Detection: A Comparative Analysis of Real and Synthetic Modifications Using InceptionV3 on the SOCOFing Dataset." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 07 (2025): 1–9. https://doi.org/10.55041/ijsrem51223.

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This study investigates the efficacy of fingerprint alteration detection using advanced deep learning techniques, specifically focusing on both real and synthetically altered fingerprint images. Utilizing the Sokoto Coventry Fingerprint Dataset (SOCOFing), which comprises over 55,000 fingerprint images from 600 African subjects, we employed the Google InceptionV3 model to classify real and altered images under varying degrees of alteration complexity. Our experimental results demonstrate a robust performance of the model, achieving an accuracy of 91.04% for detecting alterations with easy alte

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M., Ramesh kumari. "Detection and Rectification of Distorted Fingerprints." International Journal of Trend in Scientific Research and Development 2, no. 5 (2018): 1835–41. https://doi.org/10.31142/ijtsrd18185.

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One of the open come outs in fingerprint confirmation is the lack of robustness against image quality degradation. Poor quality images result in specious and missing features, thus degrading the performance of the overall system. Therefore, it is very important for a fingerprint acknowledgement system to estimate the quality and validity of the captured fingerprint images. Also the elastic distortion of fingerprints is one of the major causes for false non match. While this problem impacts all fingerprint acknowledged applications, it is especially unsafe in negative recognition applications,

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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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NIKAM, SHANKAR BHAUSAHEB, and SUNEETA AGARWAL. "CO-OCCURRENCE PROBABILITIES AND WAVELET-BASED SPOOF FINGERPRINT DETECTION." International Journal of Image and Graphics 09, no. 02 (2009): 171–99. http://dx.doi.org/10.1142/s0219467809003393.

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Perspiration phenomenon is very significant to detect the liveness of a finger. However, it requires two consecutive fingerprints to notice perspiration, and therefore may not be suitable for real time authentications. Some other methods in the literature need extra hardware to detect liveness. To alleviate these problems, in this paper, to detect liveness a new texture-based method using only the first fingerprint is proposed. It is based on the observation that real and spoof fingerprints exhibit different texture characteristics. Textural measures based on gray level co-occurrence matrix (G

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Zhang, Kang, Shu Huang, Eryun Liu, and Heng Zhao. "LFLDNet: Lightweight Fingerprint Liveness Detection Based on ResNet and Transformer." Sensors 23, no. 15 (2023): 6854. http://dx.doi.org/10.3390/s23156854.

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With the rapid development of fingerprint recognition systems, fingerprint liveness detection is gradually becoming regarded as the main countermeasure to protect the fingerprint identification system from spoofing attacks. Convolutional neural networks have shown great potential in fingerprint liveness detection. However, the generalization ability of the deep network model for unknown materials, and the computational complexity of the network, need to be further improved. A new lightweight fingerprint liveness detection network is here proposed to distinguish fake fingerprints from real ones

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Altameemi, Hayder G. A., Ahmed Abdul Azeez Ismael, and Raddam Sami Mehsen. "Hough Transform for Distinctive Edge Detection to Images in Fingerprint Recognition Matching Transformation." Webology 18, no. 2 (2021): 999–1010. http://dx.doi.org/10.14704/web/v18i2/web18369.

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Biometric Identification is a globally renowned procedure, which has been utilised to achieve a successful and accurate level of identification. In the sea of biometrics, fingerprints are deemed more popular when it comes to verification. This results from the presence of the ridges on the fingerprints that are completely exclusive to each individual. Besides that, fingerprints are expansively employed to ascertain and authenticate people individually. Therefore, this study had proposed to employ distinctive Edge Detection techniques together with the Hough Transform to match the images of the

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Diaz Pineda, Mabel Rocio, Maria Alejandra Dueñas, and Karen Dayanna Acevedo. "Fingerprints detection using neural networks suitable to physical changes of fingerprint." Revista CINTEX 22, no. 2 (2017): 35–50. http://dx.doi.org/10.33131/24222208.271.

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This working paper shows the results of finished research, using image processing techniques to improve the fingerprint obtained from a database, where the image is normalized and segmented to get only the section of the image with the fingerprint. Then, the Gabor filter is applied, and it corrects defects in ridges and valleys, allowing continuity. That way, if the fingerprint has a physical defect, the filter can correct it as long as the segment orientation to be correct. Once improved, the fingerprint, it is binarized and thinned for minutiae extraction. The false minutiae are filtered and

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Lakshmi, M. Sri, S. Sai Jayanth, Jayanth ., and Mahendra . "BIO-METRIC IDENTITY BY CONTACTLESS AND CONTACT-BASED MATCHING WITH CONSERVATIVE FINGERPRINT IMAGES." International Journal of Engineering Applied Sciences and Technology 6, no. 10 (2022): 261–67. http://dx.doi.org/10.33564/ijeast.2022.v06i10.034.

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To defend state borders and backup egovernance programs, enormous databases of contactbased fingerprints have been generated. Contactless fingerprints sensors are becoming more popular because they provide a greater cleanliness, security and accuracy. The existing method have capacity to match contactless 2D fingerprints with legacy contact-based fingerprint databases is critical to the adoption and success of such contactless fingerprint technologies. This research looks at the issue and proposes a novel method for reliably matching fingerprint scans. The project consists of a robust thin-pla

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Chen, Jiong, Heng Zhao, Zhicheng Cao, Fei Guo, and Liaojun Pang. "A Customized Semantic Segmentation Network for the Fingerprint Singular Point Detection." Applied Sciences 10, no. 11 (2020): 3868. http://dx.doi.org/10.3390/app10113868.

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As one of the most important and obvious global features for fingerprints, the singular point plays an essential role in fingerprint registration and fingerprint classification. To date, the singular point detection methods in the literature can be generally divided into two categories: methods based on traditional digital image processing and those on deep learning. Generally speaking, the former requires a high-precision fingerprint orientation field for singular point detection, while the latter just needs the original fingerprint image without preprocessing. Unfortunately, detection rates

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sree, Bhavya, Nalini T S, Deepika TA, Nagaraj ., and Jagadamba A. "Fingerprint Image Identification for Crime Detection." International Journal of Innovative Research in Information Security 9, no. 02 (2023): 10–14. http://dx.doi.org/10.26562/ijiris.2023.v0902.02.

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The identification of a person has become, crucial part in this physical world (fast growing) identification features of a person can be included iris, Fingerprints etc. The fingerprint plays an important role in crime investigation, to identify the criminals which makes easy to solve the crime. The fingerprint is collected from the crime scene. These images are stored in digital format saved in database. The image is pre-processed using techniques acquisition, Enhancement, Thinning fingerprint image features are extracted from the pre-processed image. These pre-processed data is tested and tr

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Liu, Yonghong, Baicun Zhou, Congying Han, Tiande Guo, and Jin Qin. "A Method for Singular Points Detection Based on Faster-RCNN." Applied Sciences 8, no. 10 (2018): 1853. http://dx.doi.org/10.3390/app8101853.

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Most methods for singular points detection usually depend on the orientation fields of fingerprints, which cannot achieve reliable and accurate detection of poor quality fingerprints. In this study, a new method for fingerprint singular points detection based on Faster-RCNN (Faster Region-based Convolutional Network method) is proposed, which is a two-step process, and an orientation constraint is added in Faster-RCNN to obtain orientation information of singular points. Besides, we designed a convolutional neural network (ConvNet) for singular points detection according to the characteristics

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Le, Ngoc Tuyen, Duc Huy Le, Jing-Wein Wang, and Chih-Chiang Wang. "Entropy-Based Clustering Algorithm for Fingerprint Singular Point Detection." Entropy 21, no. 8 (2019): 786. http://dx.doi.org/10.3390/e21080786.

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Fingerprints have long been used in automated fingerprint identification or verification systems. Singular points (SPs), namely the core and delta point, are the basic features widely used for fingerprint registration, orientation field estimation, and fingerprint classification. In this study, we propose an adaptive method to detect SPs in a fingerprint image. The algorithm consists of three stages. First, an innovative enhancement method based on singular value decomposition is applied to remove the background of the fingerprint image. Second, a blurring detection and boundary segmentation a

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Agarwal, Rohit, A. S. Jalal, and K. V. Arya. "A review on presentation attack detection system for fake fingerprint." Modern Physics Letters B 34, no. 05 (2020): 2030001. http://dx.doi.org/10.1142/s021798492030001x.

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Fingerprint recognition systems are susceptible to artificial spoof fingerprint attacks, like molds manufactured from polymer, gelatin or Play-Doh. Presentation attack is an open issue for fingerprint recognition systems. In a presentation attack, synthetic fingerprint which is reproduced from a real user is submitted for authentication. Different sensors are used to capture the live and fake fingerprint images. A liveness detection system has been designed to defeat different classes of spoof attacks by differentiating the features of live and fake fingerprint images. In the past few years, m

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Rani, Ishu, Deepak Sharma, Manpreet Kaur, Poonam Singla, Kanchan Chhoker, and Aishwarya Nehra. "Potential of quinoline derivatives for the detection of latent fingerprints: A review." INDIAN JOURNAL OF HETEROCYCLIC CHEMISTRY 35, no. 02 (2025): 457. https://doi.org/10.59467/ijhc.2025.35.457.

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Forensic science heavily relies on the detection and enhancement of latent fingerprints during the investigation of crime scenes. Of late, quinoline compounds, a subclass of organic heterocyclic compounds, have garnered interest in view of their use in developing fingerprints. These compounds might have a strong affinity with the amino acids and proteins present in oil remnants, which will allow them to work well with fingerprint constituents. Compositions such as 8-hydroxyquinoline and other analogs of quinoline might be useful in rendering fingerprint images cleaner and more distinct due to

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Chandra M T, Swathi, Adhithya K V, Adith A, Avani Sajeevan, and K. Muhammed Adil. "HemoDetect: Blood Group Detection from Fingerprint Using Machine Learning and Deep Learning Methodologies." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 04 (2025): 1–9. https://doi.org/10.55041/ijsrem44036.

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Fingerprints are a unique identification mechanism that is useful for determining human identity. Hardly one in more than 64,000 million people share a similar fingerprint pattern. The minute pattern of the fingerprint of each individual is unmatched with minimal possibility of similarity. The science behind detecting the blood group from the fingerprint is derived from the presence of proteins and antigens present in sweat on the ridges and grooves of the fingerprint. This paper uses advanced image processing and machine learning algorithms to compare fingerprint patterns and various blood gr

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Aggarwal, Pallavi, and Mansi Chitkara. "Detection of Metabolites in Latent Fingerprints Through Green Nanoparticles for Both Forensic Investigations and Medical Purposes." ECS Transactions 107, no. 1 (2022): 10593–602. http://dx.doi.org/10.1149/10701.10593ecst.

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Fingerprints are of core importance to the forensic science for the case investigations. The latent fingerprints are the invisible fingerprints which needs different methods to be visualized. Many methods have been developed for the visualiztion of the latent fingerprints through which the unique ridge pattern of the individual can be identified, but there is a strong requirement for the detection of sweat residues present in the latent fingerprint ridges. The latent fingerprints opens a wide scope of unexplored area in research that is beyond the scope of forensics in detecting various illici

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Cheng, Kwan H., Jacob Ajimo, and Wei Chen. "Exploration of Functionalized CdTe Nanoparticles for Latent Fingerprint Detection." Journal of Nanoscience and Nanotechnology 8, no. 3 (2008): 1170–73. http://dx.doi.org/10.1166/jnn.2008.18166.

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The potential of using water-soluble photoluminescent nanoparticles of different sizes for latent fingerprint detection has been explored. In this pilot study, green (582nm) and red (755 nm) CdTe nanocrystals coated with thioglycolic acid were used. Latent fingerprints on aluminum and glass surfaces were successfully labeled with these nanoparticles for time periods ranging from 30 min to 24 h. The labeling is probably due to the amidation reaction between the surface carboxylic groups of the nanoparticles with the amine groups of the biomaterials present in the fingerprint residues. The 582nm

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Babikir Adam, Edriss Eisa, and Sathesh. "Evaluation of Fingerprint Liveness Detection by Machine Learning Approach - A Systematic View." Journal of ISMAC 3, no. 1 (2021): 16–30. http://dx.doi.org/10.36548/jismac.2021.1.002.

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Recently, fake fingerprint detection is a challenging task in the cyber-crime sector in any developed country. Biometric authentication is growing in many sectors such as internet banking, secret file locker, etc. There spoof fingerprint detection is an essential element that is used to detect spot-on fingerprint analysis. This article focuses on the implementation and evaluation of suitable machine learning algorithms to detect fingerprint liveness. It also includes the comparative study between Ridge-let Transform (RT) and the Machine Learning (ML) approach. This article emphasis on research

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Huo, Yuanzhi, Pradini Puspitaningayu, Nobuo Funabiki, Kazushi Hamazaki, Minoru Kuribayashi, and Kazuyuki Kojima. "A Proposal of the Fingerprint Optimization Method for the Fingerprint-Based Indoor Localization System with IEEE 802.15.4 Devices." Information 13, no. 5 (2022): 211. http://dx.doi.org/10.3390/info13050211.

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Nowadays, human indoor localization services inside buildings or on underground streets are in strong demand for various location-based services. Since conventional GPS cannot be used, indoor localization systems using wireless technologies have been extensively studied. Previously, we studied a fingerprint-based indoor localization system using IEEE802.15.4 devices, called FILS15.4, to allow use of inexpensive, tiny, and long-life transmitters. However, due to the narrow channel band and the low transmission power, the link quality indicator (LQI) used for fingerprints easily fluctuates by hu

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Dr.D.Siva, Sundhara Raja, and J.Abinaya. "A Cost Effective Method for Blood Group Detection Using Fingerprints." International Journal of Advance Study and Research Work 2, no. 3 (2019): 1–11. https://doi.org/10.5281/zenodo.2591955.

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<strong><em>In this latest automated world, it has become more and more essential to keep people in a protected way. This paper proposes an important scheme of blood group detection using a fingerprint. There are five feature extraction used in the fingerprint images and represented using a mathematical model.  In this paper, we have increased the efficiency of fingerprint matching by combining GLCM based feature extraction, wavelet feature extraction, laws of texture feature extraction and minutiae feature extraction with Back Propagation Neural Network based matching. Once the feature e

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Guo, Yanyan, Xiangdong Fei, and Qijun Zhao. "Fingerprint Liveness Detection Using Multiple Static Features and Random Forests." International Journal of Image and Graphics 14, no. 04 (2014): 1450021. http://dx.doi.org/10.1142/s0219467814500211.

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It has been demonstrated that fingerprint recognition systems are susceptible to spoofing by presenting a well-duplicated synthetic such as a gummy finger. This paper proposes a novel software-based liveness detection approach using multiple static features. Given a fingerprint image, the static features, including fingerprint coarseness, first-order statistics and intensity-based features, are extracted. Unlike previous methods, the fingerprint coarseness is modeled as multiplicative noise rather than additive noise and is extracted by cepstral analysis. A random forest classifier is employed

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Nguyen, Thi, Eunsoo Park, Xuenan Cui, Van Nguyen, and Hakil Kim. "fPADnet: Small and Efficient Convolutional Neural Network for Presentation Attack Detection." Sensors 18, no. 8 (2018): 2532. http://dx.doi.org/10.3390/s18082532.

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The rapid growth of fingerprint authentication-based applications makes presentation attack detection, which is the detection of fake fingerprints, become a crucial problem. There have been numerous attempts to deal with this problem; however, the existing algorithms have a significant trade-off between accuracy and computational complexity. This paper proposes a presentation attack detection method using Convolutional Neural Networks (CNN), named fPADnet (fingerprint Presentation Attack Detection network), which consists of Fire and Gram-K modules. Fire modules of fPADnet are designed followi

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F.W. Onifade, Olufade, Paul Akinde, and Folasade Olubusola Isinkaye. "Circular Gabor wavelet algorithm for fingerprint liveness detection." Journal of Advanced Computer Science & Technology 9, no. 1 (2020): 1. http://dx.doi.org/10.14419/jacst.v9i1.29908.

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Biometrics usage is growing daily and fingerprint-based recognition system is among the most effective and popular methods of personality identification. The conventional fingerprint sensor functions on total internal reflectance (TIR), which is a method that captures the external features of the finger that is presented to it. Hence, this opens it up to spoof attacks. Liveness detection is an anti-spoofing approach that has the potentials to identify physiological features in fingerprints. It has been demonstrated that spoof fingerprint made of gelatin, gummy and play-doh can easily deceive s

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Sweta Raut, Dr, Miss Gunjan Mankar, Miss Sharayu Nistana, Miss Vasundhara Shivhare, Miss Shreya Sayare, and Miss Saloni Deorankar. "Blood Group Detection Using Fingerprint." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 03 (2025): 1–9. https://doi.org/10.55041/ijsrem43201.

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Blood group identification is crucial for safe medical procedures, but traditional techniques are based on invasive blood draws, which are risky and inconvenient. This research presents a new, non-invasive method to identify ABO and Rh blood groups from fingerprints. By taking advantage of the biochemical residues in fingerprint sweat, which include blood group-specific antigens, we integrate Fourier-transform infrared (FTIR) spectroscopy and machine learning to identify blood groups. 200 participants with known blood groups provided spectroscopic analysis fingerprint samples to distinguish sp

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Allred, Clay E., Tao Lin, and E. Roland Menzel. "Lipid-Specific Latent Fingerprint Detection: Fingerprints on Currency." Journal of Forensic Sciences 42, no. 6 (1997): 14251J. http://dx.doi.org/10.1520/jfs14251j.

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Kirfel, Alexander, Tobias Scheer, Norbert Jung, and Christoph Busch. "Robust Identification and Segmentation of the Outer Skin Layers in Volumetric Fingerprint Data." Sensors 22, no. 21 (2022): 8229. http://dx.doi.org/10.3390/s22218229.

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Despite the long history of fingerprint biometrics and its use to authenticate individuals, there are still some unsolved challenges with fingerprint acquisition and presentation attack detection (PAD). Currently available commercial fingerprint capture devices struggle with non-ideal skin conditions, including soft skin in infants. They are also susceptible to presentation attacks, which limits their applicability in unsupervised scenarios such as border control. Optical coherence tomography (OCT) could be a promising solution to these problems. In this work, we propose a digital signal proce

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Vasil’ev, V. A., T. A. Ermakova, Yu A. Druzhinin, I. B. Afanas’ev, and Yu T. Yudina. "On the Development of New Forensic Tools for Detection of Human Skin Prints." Theory and Practice of Forensic Science 16, no. 4 (2022): 40–48. http://dx.doi.org/10.30764/1819-2785-2021-4-40-48.

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The article reviews the main physical and physicochemical factors influencing the three-component system “fingerprint powder – prints bearing surface – sweat and grease print substance”. The authors propose new model compositions of fingerprint powders considering the reviewed common patterns: non-magnetic and luminescent magnetic. The features of prints bearing surfaces and developed fingerprint powders have been evaluated by applying electronic microscopy methods (scanning and probe microscopy). The authors have proven that the use of nano- and ultra disperse materials in the developed compo

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Li, Xinting, Weijin Cheng, Chengsheng Yuan, Wei Gu, Baochen Yang, and Qi Cui. "Fingerprint Liveness Detection Based on Fine-Grained Feature Fusion for Intelligent Devices." Mathematics 8, no. 4 (2020): 517. http://dx.doi.org/10.3390/math8040517.

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Currently, intelligent devices with fingerprint identification are widely deployed in our daily life. However, they are vulnerable to attack by fake fingerprints made of special materials. To elevate the security of these intelligent devices, many fingerprint liveness detection (FLD) algorithms have been explored. In this paper, we propose a novel detection structure to discriminate genuine or fake fingerprints. First, to describe the subtle differences between them and take advantage of texture descriptors, three types of different fine-grained texture feature extraction algorithms are used.

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Jadaan Abed, Abdulrasool, and Dhahir Abdulhadi Abdullah. "An Automated Fingerprint Image Detection and Localization Approach-based Unsupervised Learning Algorithms using Low-quality Biometrics Plam Data." JOIV : International Journal on Informatics Visualization 8, no. 3-2 (2024): 1635. https://doi.org/10.62527/joiv.8.3-2.1665.

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In this study, fingerprint identification and classification of low-quality fingerprints have been analyzed accordingly. As technology advances and methodologies evolve, staying at the forefront of research and innovation is imperative. The challenges addressed in this paper provide a foundation for future investigations and underscore the importance of developing resilient and adaptable biometric systems for real-world applications. The quest for accurate, efficient, and robust fingerprint identification in adverse conditions is a testament to the continuous evolution and refinement of machin

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Bond, John W. "Maximising the Opportunities to Detect Domestic Burglary with DNA and Fingerprints." International Journal of Police Science & Management 9, no. 3 (2007): 287–98. http://dx.doi.org/10.1350/ijps.2007.9.3.287.

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The impact on the detection and reduction of domestic burglary by a prioritisation of forensic resources and processing over a six-month study period is examined. Targets were set and monitored for the twin factors of increased attendance at crime scenes and increased timeliness of processing both DNA and fingerprint samples. The results showed that it is possible to increase the number of primary detections derived from DNA and fingerprints with the DNA increase being statistically significant. This increase was accompanied by a decrease in reported domestic burglaries. After its completion,

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Yoon, Clara E., Ossian O’Reilly, Karianne J. Bergen, and Gregory C. Beroza. "Earthquake detection through computationally efficient similarity search." Science Advances 1, no. 11 (2015): e1501057. http://dx.doi.org/10.1126/sciadv.1501057.

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Seismology is experiencing rapid growth in the quantity of data, which has outpaced the development of processing algorithms. Earthquake detection—identification of seismic events in continuous data—is a fundamental operation for observational seismology. We developed an efficient method to detect earthquakes using waveform similarity that overcomes the disadvantages of existing detection methods. Our method, called Fingerprint And Similarity Thresholding (FAST), can analyze a week of continuous seismic waveform data in less than 2 hours, or 140 times faster than autocorrelation. FAST adapts a

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Wu, Baiyang, Shuo Zhang, Weinan Gao, Yong Bi, and Xiaosong Hu. "A Method for Fingerprint Edge Enhancement Based on Radial Hilbert Transform." Electronics 13, no. 19 (2024): 3886. http://dx.doi.org/10.3390/electronics13193886.

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Fingerprints play a significant role in various fields due to their uniqueness. In order to effectively utilize fingerprint information, it is necessary to enhance image quality. This paper introduces a method based on Radial Hilbert transform (RHLT), which simulates the vortex filter using the point spread function (PSF) of spiral phase plate (SPP) with a topological charge l=1, for fingerprint edge enhancement. The experimental results show that the processed fingerprint image has more distinct edges, with an increase in information entropy and average gradient. Unlike classical edge detecti

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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

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Wang, Chunwei, Lina Yu, Huixian Chang, Sheng Shen, Fang Hou, and Yingwei Li. "Application Research of File Fingerprint Identification Detection Based on a Network Security Protection System." Wireless Communications and Mobile Computing 2020 (November 30, 2020): 1–14. http://dx.doi.org/10.1155/2020/8841417.

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A DLP (data loss prevention) system usually arranges network monitors at the network boundary to perform network traffic capture, file parsing, and strategy matching procedures. Strategy matching is a key process to prevent corporate secret-related documents from leaking. This paper adopts the document fingerprint similarity detection method based on the SimHash principle and customizes the KbS (Keyword-based SimHash) fingerprint, PbS (Paragraph-based SimHash) fingerprint, and SoP (SimHash of Paragraph) fingerprint, three different feature extraction SimHash algorithms for strategy matching to

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Boonyaras, P., S. Boonpang, and K. Dangudom. "Latent fingerprint detection using fluorescent powder dusting technique." Journal of Physics: Conference Series 2653, no. 1 (2023): 012075. http://dx.doi.org/10.1088/1742-6596/2653/1/012075.

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Abstract This study examined the use of fluorescent powder in detecting latent fingerprints through the dusting method. Five colors of fluorescent powder (orange, green, blue, green-yellow, and red) were applied to photo papers of six colors (green, red, blue, yellow, white, and black). The fluorescence of latent fingerprints was detected using various light sources including UV LED, blue LED, green LED, red LED, warm white, and cold white. The spectra of the light source and the fluorescence intensity of the dusting powder were analyzed to determine their influence on the appearance of latent

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Coulson, Sophie, Sönke Dangendorf, Jerry X. Mitrovica, Mark E. Tamisiea, Linda Pan, and David T. Sandwell. "A detection of the sea level fingerprint of Greenland Ice Sheet melt." Science 377, no. 6614 (2022): 1550–54. http://dx.doi.org/10.1126/science.abo0926.

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Rapid melting of ice sheets and glaciers drives a unique geometry, or fingerprint, of sea level change. However, the detection of individual fingerprints has been challenging because of sparse observations at high latitudes and the difficulty of disentangling ocean dynamic variability from the signal. We predict the fingerprint of Greenland Ice Sheet (GrIS) melt using recent ice mass loss estimates from radar altimetry data and model reconstructions of nearby glaciers and compare this prediction to an independent, altimetry-derived sea surface height trend corrected for ocean dynamic variabili

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Sravani, P. S. L. "Robust Fingerprint Verification-Using Real Time Security Alerts." International Journal for Research in Applied Science and Engineering Technology 13, no. 3 (2025): 1753–59. https://doi.org/10.22214/ijraset.2025.67644.

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This work presents Robust Fingerprint Authentication with Real-Time Security Alerts, a biometric authentication system that integrates Aadhaar-based identity verification, liveness detection, and real-time SMS notifications. Traditional fingerprint authentication systems store biometric data persistently, increasing the risk of breaches and unauthorized access. To address this, the proposed system ensures immediate deletion of fingerprint data after verification, enhancing security and user privacy. Advanced image processing techniques and deep learning models are employed for liveness detecti

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Amriana, Amriana, Andi Hendra, and Arfiah Bakhtiar. "Rancang Bangun Sistem Presensi Menggunakan Sidik Jari (Studi Kasus Pada Lembaga Pemasyarakatan Klas II-A Palu)." ScientiCO : Computer Science and Informatics Journal 1, no. 1 (2019): 1. http://dx.doi.org/10.22487/j26204118.2018.v1.i1.11897.

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Dermatoglyphic has been widely applied to recognize a person's identity, because people basically have something unique or characteristic possessed only by themselves. This raises the idea of making it a unique identity. This is useful for employees presence applications, especially at Lembaga Pemasyarakatan Klas IIA Palu which is still doing manual presence. This system provides the division of labor time and wereable to detect the fingerprints of employees using a fingerprint scanner. The system was made in several stages of the input fingerprint image, binarization fingerprint image, finger

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Doroz, Rafal, Krzysztof Wrobel, and Piotr Porwik. "An accurate fingerprint reference point determination method based on curvature estimation of separated ridges." International Journal of Applied Mathematics and Computer Science 28, no. 1 (2018): 209–25. http://dx.doi.org/10.2478/amcs-2018-0016.

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AbstractThis paper presents an effective method for the detection of a fingerprint’s reference point by analyzing fingerprint ridges’ curvatures. The proposed approach is a multi-stage system. The first step extracts the fingerprint ridges from an image and transforms them into chains of discrete points. In the second step, the obtained chains of points are processed by a dedicated algorithm to detect corners and other points of highest curvature on their planar surface. In a series of experiments we demonstrate that the proposed method based on this algorithm allows effective determination of

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Kumar, Ravinder, Pravin Chandra, and M. Hanmandlu. "Fingerprint Singular Point Detection Using Orientation Field Reliability." Advanced Materials Research 403-408 (November 2011): 4499–506. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.4499.

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Singular point detection is the most important step in Automatic Fingerprint Identification System (AFIS) and is used in fingerprint alignment, fingerprint matching, and particularly in classification. The computation of orientation field of a fingerprint can be verified by computing orientation field reliability. The most unreliable portion in orientation field can be the possible location of singular points. In this paper we have proposed a novel algorithm for detecting singular points using reliability of the fingerprint orientation field. Experimental results show that the proposed algorit

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Basha, P. Masoom. "A DEEP LEARNING FRAMEWORK FOR BLOOD GROUP DETECTION FROM FINGERPRINT PATTERNS." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 06 (2025): 1–9. https://doi.org/10.55041/ijsrem50135.

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Abstract —The accurate and timely determination of an individual's blood group is crucial in medical diagnostics, emergency care, and transfusion medicine. Traditional methods for blood group detection involve invasive procedures such as blood sampling and laboratory testing, which can be time- consuming, resource-intensive, and sometimes impractical in critical or remote scenarios. In recent years, biometric characteristics have gained increasing attention as potential indicators of physiological and genetic traits. Among these, fingerprint patterns have shown correlations with genetic marker

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Douiri, Hanen, Marwa Abid, Lamia Rzouga Haddada, et al. "Strongly Fluorescent Blue-Emitting La2O3: Bi3+ Phosphor for Latent Fingerprint Detection." Materials 17, no. 17 (2024): 4217. http://dx.doi.org/10.3390/ma17174217.

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Blue-emitting bismuth-doped lanthanum oxide (La2O3: Bi3+) with various concentrations of Bi was synthesized using the sol–gel combustion method and used for visualization of latent fingerprints (LFPs). An X-ray diffraction (XRD) study revealed the hexagonal structure of the phosphors and total incorporation of the bismuth in the La2O3 matrix. Field Emission Scanning Electron Microscopy (FE-SEM) and Fourier Transform Infrared Spectroscopy (FTIR) were used to study the morphology and the relative vibrations of the synthesized samples. Photoluminescence (PL) studies showed strong blue emission ar

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