Personal Identification Method Research Articles

Finger Knuckle Print Recognition using MMDA with Fuzzy Vault

Currently frequent biometric scientific research such as with biometric applications like face, iris, voice, hand-based biometrics traits like palm print and fingerprint technique are utilized for spotting out the persons. These specific biometrics habits have their own improvement and weakness so that no particular biometrics can adequately opt for all terms like the accuracy and cost of all applications. In recent times, in addition, to distinct with the hand-based biometrics technique, Finger Knuckle Print (FKP) has been appealed to boom the attention among biometric researchers. The image template pattern formation of FKP embraces the report that is suitable for spotting the uniqueness of individuality. This FKP trait observes a person based on the knuckle print and the framework in the outer finger surface. This FKP feature determines the line anatomy and finger structures which are well established and persistent throughout the life of an individual. In this paper, a novel method for personal identification will be introduced, along with that data to be stored in a secure way has also been proposed. The authentication process includes the transformation of features using 2D Log Gabor filter and Eigen value representation of Multi-Manifold Discriminant Analysis (MMDA) of FKP. Finally, these features are grouped using k-means clustering for both identification and verification process. This proposed system is initialized based on the FKP framework without a template based on the fuzzy vault. The key idea of fuzzy vault storing is utilized to safeguard the secret key in the existence of random numbers as chaff pints

A Study of Personal Recognition Method Based on EMG Signal.

With the increasing development of internet, the security of personal information becomes more and more important. Thus, variety of personal recognition methods have been introduced to ensure persons' information security. Traditional recognition methods such as Personal Identification Number (PIN), or Identification tag (ID) are vulnerable to hackers. Then the biometric technology, which uses the unique physiological characteristics of human body to identify user information has been proposed. But the biometrics widely used at present such as human face, fingerprint, iris, and voice can also be forged and falsified. The biometric with living body features such as electromyography (EMG) signal is a good method to achieve aliveness detection and prevent the spoofing attacks. However, there are few studies on personal recognition based on EMG signal. According to the application context, personal recognition system may operate either in identification mode or verification mode. In the personal identification mode, the system recognizes an individual by searching the templates of all the users in the database for a match. While in the personal verification mode, the system validates a person's identity by comparing the captured features with her or his own template(s) stored in the system database. In this paper, both EMG-based personal identification method and EMG-based personal verification method are investigated. First, the Myo armband is placed on the right forearm (specifically, the height of the radiohumeral joint) of 21 subjects to collect the surface EMG signal under hand-open gesture. Then, two different methods are proposed for EMG-based personal identification, i.e., personal identification method based on Discrete Wavelet Transform (DWT) and ExtraTreesClassifier, and personal identification method based on Continuous Wavelet Transform (CWT) and Convolutional Neural Networks (CNN). Experiments with 21 subjects show that the identification accuracy of this two methods can achieve 99.206% and 99.203% respectively. Then based on the identification method using CWT and CNN, transfer learning algorithm is adopted to solve the model update problem when new data is added. Finally, an EMG-based personal verification method using CWT and siamese networks is proposed. Experiments show that the verification accuracy of this method can achieve 99.285%.

Chipping as a Method of Personal Identification Within the Framework of Criminalistics

This article explores the issues of objective possibility of using chipping as a method of personal identification within the framework of criminalistics. This article examines the operating principle of the microchip, its functions at the present stage of the development of science. Applicable nature of this method for maintaining the effective work of law enforcement agencies is substantiated based on this research. The article analyzes the problem of the correlation of implanting the microchips into the human body with the concept of protecting the rights and freedoms of each person and citizen.

Intraoral Scanners in Personal Identification of Corpses: Usefulness and Reliability of 3D Technologies in Modern Forensic Dentistry

Aims:This study aims to verify the applicability of modern dental technologies and their related principles of use to the forensic sciences in the field of personal identification.Background:Personal identification has always had a major role in many legal and administrative actions regarding both living and death beings. The techniques used are much less advanced than the technologies potentially available.Objective:Modern technologies, available to the daily dental clinic practice, as intraoral scanners, combined in particular to the specialist skill in orthodontics, can help redefine the methods of personal identification according to the levels of accuracy, trueness and feasibility greater than those applied in traditional forensic dentistry.Methods:23 corpses (12F;11M) have been selected for intraoral scanning with the Carestream 3500®digital device. The superimposition of initial and late digital models, digital models and radiographs (orthopantomography and full mouth periapical films) has been evaluated to verify the stability of some structures as palatal rugae after death and to assess intraoral scanning as a successful comparative method between antemortem and post-mortem records (digital models or radiographs). Obtained results were subjected to statistical analysis by the t-student test and X-square test with Yates correction (p<0.05).Results:After death, palatal rugae significatively change especially in mouths with restorations/prosthesis/missing teeth. The percentages of correct matching between scans and radiographs are very higher (up 90%; p<0.05).Conclusion:This study has been set up to study and develop new, reliable and fast methods of personal identification that can surpass many of the issues seen with the other techniques by a modern rugoscopy, a modern radiographic-digital comparison and virtual oral autopsy.

Intraoral Scanners in Personal Identification of Corpses: Usefulness and Reliability of 3D Technologies in Modern Forensic Dentistry

Aims:This study aims to verify the applicability of modern dental technologies and their related principles of use to the forensic sciences in the field of personal identification.Background:Personal identification has always had a major role in many legal and administrative actions regarding both living and death beings. The techniques used are much less advanced than the technologies potentially available.Objective:Modern technologies, available to the daily dental clinic practice, as intraoral scanners, combined in particular to the specialist skill in orthodontics, can help redefine the methods of personal identification according to the levels of accuracy, trueness and feasibility greater than those applied in traditional forensic dentistry.Methods:23 corpses (12F;11M) have been selected for intraoral scanning with the Carestream 3500®digital device. The superimposition of initial and late digital models, digital models and radiographs (orthopantomography and full mouth periapical films) has been evaluated to verify the stability of some structures as palatal rugae after death and to assess intraoral scanning as a successful comparative method between antemortem and post-mortem records (digital models or radiographs). Obtained results were subjected to statistical analysis by the t-student test and X-square test with Yates correction (p<0.05).Results:After death, palatal rugae significatively change especially in mouths with restorations/prosthesis/missing teeth. The percentages of correct matching between scans and radiographs are very higher (up 90%; p<0.05).Conclusion:This study has been set up to study and develop new, reliable and fast methods of personal identification that can surpass many of the issues seen with the other techniques by a modern rugoscopy, a modern radiographic-digital comparison and virtual oral autopsy.

Palm vein recognition based on competitive coding scheme using multi-scale local binary pattern with ant colony optimization

Among the various biometric traits that can be extracted from the hand, the palm vein structure that represents a reliable and secure source for identifying and/or verifying the identity of a person. Several recognition methods were proposed in the literature exploiting this modality; among them, the attractive approaches based on a competitive coding. Aiming to further improve the performance of these approaches, this paper presents a novel palm vein recognition method for personal authentication and identification based on a competitive coding scheme using Multi-scale local binary pattern (MLBP) with Ant colony optimization (ACO). ACO allows to override potential blocking points related to image quality or contrast problems that can be encountered with images from the Near infrared spectral band. The pre-processed images will be then sorted with a competitive coding scheme using MLBP; where the final image will be composed of the winning code from the different MLBP images. The matching process for making-decision is then performed using Kullback-Leibler divergence and Jaccard distance. The experimental results obtained on MS-PolyU database has shown that the proposed method achieves improved performances for both identification and verification modes up to 99.64% in terms of CIR for the identification and 0.00078% in terms of EER for the verification; and also outperforms the state-of-the-art methods.

Accuracy of Trained Community-based Rehabilitation Volunteers in Identification and Appropriate Referral of Adults with Perceived Visual Disability in an Urban-slum Setting in Southern India

ABSTRACT Purpose The integration of primary eyecare into existing primary healthcare systems requires simple yet effective tools that do not overburden the grass-root level worker. The objective of this study was to test the accuracy of a questionnaire-based tool administered by trained community-based rehabilitation volunteers (CBRVs) in identifying persons with visual disability, proportions accessing referral pathway and barriers to uptake of eyecare services. Methods CBRVs working in the urban-slum service area of a teaching hospital were trained in administering a questionnaire-based tool derived from the World Health Organization (WHO) “Training in the community for people with disabilities” to a responsible adult member of the household. Post-training, they screened and referred adults with perceived visual problems. This tool was tested against two reference standards: (i) history of visual disability elicited by ophthalmologist; (ii) pre-set visual acuity and diagnosis criteria. Results Ten CBRVs screened 950 individuals of whom 805 (84.7%) were examined by an optometrist and ophthalmologist. Sensitivity and specificity of this method were 75% (95% CI 72–78%), 95.8% (95% CI 94–98%) respectively, using history and 60.2% (95% CI 57–63%), 91.8% (95% CI 90–94%) using clinical criteria as reference standard. Referral pathway was used by 91/221 (41.2%) referred individuals. The commonest barriers to accessing eye care were ‘did not feel the need’ (32.2%) and ‘busy with work/household responsibilities’ (30.2%). Conclusions This questionnaire-based tool administered by grass-root level health workers to a responsible adult member of the family may be a promising screening method for identification and appropriate referral of persons with visual disability in the community.

Trustworthy Method for Person Identification in IIoT Environments by Means of Facial Dynamics

In industrial Internet of Things (IIoT) environments, dependability of a complex manufacturing process in which human operators play a key role can be improved by identity recognition/authentication of whoever is involved in various stages of a production process, according to where and when he/she is supposed to be. To this aim, we propose an approach that exploits the dynamic appearance and the time-dependent local features characterizing the face of an individual during speech utterance with regard to their spatial and temporal components. The proposed method models these dynamic facial patterns captured from edge Internet of Things devices by means of the Local Binary Pattern on Three Orthogonal Planes descriptor, which effectively extract both face's local features and movement at the fog level of the architecture. A deep feedforward network available in the cloud is trained and optimized to match the extracted features to a reference database. The achieved results highlight state-of-the-art performances of the proposed method with regard to robustness and trustworthiness of identification, especially for challenging IIoT scenarios.

EEG-based personal identification method using unsupervised feature extraction and its robustness against intra-subject variability

Objective. Brain activity signals are possible biomarkers for personal authentication. However, they are inherently variable due to measurement-environment factors and subject-dependent factors; electroencephalography (EEG) signals could be different in days even for the same task, subject, and experimental settings. This variability could cause loss of consistency of the signals across multiple measurements of a single subject, and hence decrease the performance of EEG-based personal identification. In this study, we evaluated the influence of the variability on personal EEG features by using our original EEG dataset. Approach. We collected EEG signals in twenty subjects across four rounds (morning and afternoon daily for two days). At each round, we reinstalled an EEG cap on the subjects’ scalps. To extract personal EEG features that were invariant across the sessions, we proposed unsupervised learning methods; common dictionary learning and t-distributed stochastic neighbor embedding. To assess the performance of personal identification, we compared two different experimental settings; test data recorded in the same round as the training data (Setting SR) and test data recorded in different rounds (Setting DR). Main results. The performance in SR was better than that in DR, suggesting that features dependent on the rounds were dominant. However, the 40% accuracy rate in DR, which is significantly higher than the chance level, suggests that our proposed method robustly extracted the personal features against the variability, in most cases. Furthermore, we also evaluated the performance of a problem, which involved detecting individuals who were not registered in the authentication system. In this problem, we obtained a similar result that the variability for the rounds influenced the performance. However, we obtained a good performance in the detection of some unknown subjects even in DR. Significance. We found the variability in EEG data actually affected the personal features that were used for personal identification. Even considering the variability in EEG data, however, we found our proposed method is applicable in personal authentication scenarios, i.e. personal identification and unknown detection.

Person Identification Based on Micro-Doppler Signatures of Sit-to-Stand and Stand-to-Sit Movements Using a Convolutional Neural Network

This letter presents a method for person identification based on sit-to-stand and stand-to-sit movements using micro-Doppler radar measurements and a convolutional neural network (CNN). Two 24-GHz micro-Doppler radar systems placed directly above or behind participants will be used to measure the sit-to-stand and stand-to-sit movements of 10 participants. Images of the micro-Doppler signatures will be generated by subjecting the signals received by the radar to short-time Fourier transform. The generated images will then be used as input for the CNNs for training and evaluation purposes. The experiments verified the ability of the method to accurately identify people by measuring both their sit-to-stand and stand-to-sit movements. The identification accuracies for the sit-to-stand and stand-to-sit measurements were 93.6% and 94.9%, respectively, using the data of the radar placed above the participant, whereas the accuracy when placing the radar behind the participant was 92.9% for the sit-to-stand and 93.9% for the stand-to-sit movements. The obtained results will prove that both the horizontal and vertical directions of the velocities of both movements include information that can be used to identify individuals, and this information can be obtained with micro-Doppler radar systems.

Stature estimation in forensic examinations using regression analysis: A likelihood ratio perspective

For the identification of decomposed dead bodies and skeletal remains, estimation of stature is of utmost importance. In estimating stature from the percutaneous bone lengths or skeletal remains, regression analysis has been the method of choice. Technically, as the regression line is just the best fit to the data, the estimate of stature differs from the actual stature, and this difference is reported in terms of the root mean square error (RMSE). The estimate using regression analysis is probabilistic in nature and there is a confidence interval about the prediction. This interval is mostly not reported in various studies, neither are the probable errors in estimation. In the likelihood ratio approach, absolute “matching” or “identification” is not possible and therefore, only the quantitative strength of evidence (strength of association in the present context) is given.The sample for the present study comprised of 344 young adults (172 females and 172 males) residing in the Shimla city of Himachal Pradesh State of north India. The data have been generated from anthropometric measurements of seven percutaneous bone lengths besides stature. The present study reports the regression equations for stature estimation as traditionally calculated, but additionally, it signifies the determination of the confidence intervals of the regression line as well as the confidence intervals of the prediction of stature. The study also shows that for the likelihood ratio estimation, the regression analysis needs to be flipped, i.e. instead of using regression of stature versus bone length; the regression of bone length versus stature should be used.Practical application of finding the likelihood ratio of a recovered bone to be associated with two missing persons of known stature has also been discussed in the current study. This approach is further extended to a general scenario, where the likelihood of a person of known stature is evaluated with reference to any other person chosen at random from the relevant population. The likelihood ratios arrived at, have been found to be generally low, meaning that the strength of association of stature and percutaneous bone length is not very high, and combining likelihood ratios from different methods of personal identification may be needed.

Assessment on Extraction and Matching of Finger Vein and Iris Pattern based Authentication System

Biometrics uses human behavioral features for personal identification and has become most popular and promising alternatives than the traditional methods. The vein pattern is hidden inside the body and hence the problem of forgery in vein is consequently reduced when compared to fingerprint. Iris is one of the most reliable biometric traits due to its uniqueness and stability. The uniqueness of iris texture comes from the random and complex structures such as furrows, ridges, crypts, rings, corona, and freckles etc. which are formed during gestation. Often iris is combined with other biometric features for robust biometric systems. The finger vein pattern acquired under infrared light is used to design an accurate personal authentication system. The personal identification method based on vein extract the patterns from an unclear original image and line tracking operations with randomly varied start points are repeatedly carried out. This paper reviews various techniques introduced in finger vein and iris recognition system. This paper mainly focuses in introduction about finger vein and iris pattern, survey of existing research works done in the process under finger vein combined with iris recognition such as image acquisition, vein and iris enhancement, vein and iris pattern extraction and vein and iris pattern matching. Finally the challenges and future work are discussed in order to improve the left finger vein pattern with right iris and right finger vein pattern with left iris recognition.

Evaluation for Correlation of Cheiloscopy and Dermatoglyphics in Gender Determination

Background: Identification of the suspect, living or dead with the help of physical charachteristics play a vital role in forensic science. Improved methods of gender determination and personal identification are important in solving criminal cases. Cheiloscopy and dactyloscopy have been proved to be of use in personal identification. The present study aims to evaluate correlation of Cheiloscopy and Dermatoglyphics in gender determinationMaterials and Method: The study was carried out from January 2017 to January 2019 on 2112 individuals (1056 males and 1056 females) aged from 15 to 60 years in KMCT Dental College, Calicut. For lip print analysis Suzuki and Tsuchihashi classification was followed. For finger print analysis impression of all the fingers were taken. For analysis, the images were cropped and abode photoshop software was used.Results: Type 1 and 1’ lip groove patterns were found to be predominant among males.Type 4 and Type 5 lip groove patterns were found to be predominant among females. Loop finger print patterns were found to be predominant among males.Whorl finger print patterns were found to be predominant among females. Positive correlation (+0.80) was found between loop finger print pattern and Type 1’ lip print pattern in males which is statistically significant (p=0.003).Positive correlation (+0.75) was found between whorl finger print pattern and Type IV lip groove pattern in females which is statistically significant. (p=0.005)Conclusion: There was definite correlation of Cheiloscopy and Dermatoglyphics in gender determination

New method for identification of persons using geometry foot outline

In this study we try to improve existing recognition rates using plantar surface of foot to extract 19 local geometrical features based on anatomical points and axes, in order to extract informations and relationships required to perform a biometric system for identifying individuals. Before the primary data collection, a pilot study was conducted to assess the precision of stature acquisition and foot measurements. A computer database has been constructed taking measurements from feet pictures of 102 volunteers using the measuring tool in Photofilter. Using the measurements with ±0.38 like error margin and searching through it shows that each foot is unique. This study also showed that each measurement parameter's has an identification percentage and the highest percentages were noted for the parallel and diagonal lengths measurements. To validate our database and our results we tried to study the relation between the stature and some foot measurements using a linear equation of regression.

New method for identification of persons using geometry foot outline

In this study we try to improve existing recognition rates using plantar surface of foot to extract 19 local geometrical features based on anatomical points and axes, in order to extract informations and relationships required to perform a biometric system for identifying individuals. Before the primary data collection, a pilot study was conducted to assess the precision of stature acquisition and foot measurements. A computer database has been constructed taking measurements from feet pictures of 102 volunteers using the measuring tool in Photofilter. Using the measurements with ±0.38 like error margin and searching through it shows that each foot is unique. This study also showed that each measurement parameter's has an identification percentage and the highest percentages were noted for the parallel and diagonal lengths measurements. To validate our database and our results we tried to study the relation between the stature and some foot measurements using a linear equation of regression.

Population Genetics in Malaysia and Japanese Populations Using Power Plex Y23 System.

Population flow between Southeast Asian countries and Japan continues to gather pace. Accordingly, the number of foreigners involved in incidents in Japan has markedly increased, which means that forensic dentistry is now increasingly being faced with the need to analyze DNA from persons of non-Japanese extraction. The DNA test currently used for personal identification mainly utilizes short tandem repeats (STRs) on autosomal chromosomes and the Y-chromosome. This test was developed for use in personal identification, not for distinguishing among races; nonetheless, the standard method for personal identification is often used because the procedure has been established. To determine the degree to which racial differences can be distinguished by standard DNA analysis, 23 STRs located on the Y chromosome were investigated in 218 Malay and 426 Japanese males. The frequencies of each STR were calculated in the two populations. The difference in the power of discrimination between the Malay and Japanese populations ranged from a minimum of 0.01 to a maximum of 0.27; the difference in polymorphic information content ranged from 0.01 (minimum) to 0.23 (maximum). No major differences were noted in the polymorphisms in these two Mongoloid populations, but the distributions of the 17 STRs differed significantly. Short tandem repeat types demonstrating a likelihood of racial differences were identified in 14 of the STRs. Race-specific STR types were identified in 10 STRs. These results suggest that the likelihood of Malay or Japanese genetic background can be judged based on Y-chromosome STR test results.

THE PROCESS OF SCIENTIFIC KNOWLEDGE INTEGRATION IN CRIME PREVENTION AND TRENDS OF MEDICAL CRIMINALISTICS DEVELOPMENT IN UKRAINE IN XIX – EARLY XX CENTURY

The aim: To carry out a historical review of the formation and development of medical forensics in the XIX - early XX century in Ukraine, as well as to identify its trends at the present stage. Materials and methods: The article is based on the study of archival and published materials, the results of integrating expert judgments, judicial practice and regulatory acts of the Ministry of Health of Ukraine, interviewing investigators and court experts. In the course of the research a system of scientific methods has been used: historical, comparative, terminological analysis, formal-logical, sociological. Conclusions: In the XIX and early XX centuries, the foundations for the formation of medical criminalistics were laid, which facilitated the development of forensic medicine, criminalistics and forensic examination. Special medical knowledge is widely used in investigative, judicial and expert practice. The synthesis of medical and forensic knowledge enhanced the development of a method of personal identification, based on his/her genetic properties, the formation of molecular genetic examination, the study of individual objects at the modern level.

Home Security using Face Recognition Technology

Face is the easiest way to penetrate each other's personal identity. Face recognition is a method of personal identification using the personal characteristics of an individual to decide the identification of a person. The method of human face recognition consists basically of two levels, namely face detection and face recognition. There are three types of methods that are currently popular in the developed face recognition pattern, those are Eigen faces algorithm, Fisher faces algorithm and CNN neural network for face recognition

Automatic segmentation of blood vessels in retinal images using 2D Gabor wavelet and sub-image thresholding resulting from image partition

The retina features the only blood vessel network in humans that is visible in a non-invasive imaging method. This, along with uniqueness and stability throughout life in healthy subjects, makes it an ideal target for personal identification methods in biometric systems and also for the screening and diagnosis of diseases. However, retinal images usually present low contrast of the vessels in relation to the retinal background and high level of noise stemming mainly from the acquisition process. This work aims to reduce noise and improve contrast to increase the accuracy of retinal vessel segmentation. 2D Gabor wavelet (GW) is usually employed to reduce noise and improve vessel contrast in relation to the background. In this work, it is proposed that, before the thresholding, the GW output images are partitioned into 20 sub-images in such a way that each can be treated independently. The images used were obtained from two public databases, DRIVE and STARE, and the algorithm was developed in MatLab® environment. The proposed approach reached an accuracy of 96.15%, sensitivity of 73.42%, and specificity of 98.30% in DRIVE. In STARE, the accuracy was 94.87%, sensitivity 71.74%, and specificity 96.93%. The methods proposed by the authors indicate gains in accuracy and specificity in the automatic detection of retinal vessels, in both databases used, when compared with those in the main published works. The accuracy is also higher than the 94.73% in interobserver accuracy previously determined as the gold standard.

Person identification using fusion of iris and periocular deep features

A novel method for person identification based on the fusion of iris and periocular biometrics has been proposed in this paper. The challenges for image acquisition for Near-Infrared or Visual Wavelength lights under constrained and unconstrained environments have been considered here. The proposed system is divided into image preprocessing data augmentation followed by feature learning for classification components. In image preprocessing an annular iris, the portion is segmented out from an eyeball image and then transformed into a fixed-sized image region. The parameters of iris localization have been used to extract the local periocular region. Due to different imaging environments, the images suffer from various noise artifacts which create data insufficiency and complicate the recognition task. To overcome this situation, a novel method for data augmentation technique has been introduced here. For features extraction and classification tasks well-known, VGG16, ResNet50, and Inception-v3 CNN architectures have been employed. The performance due to iris and periocular are fused together to increase the performance of the recognition system. The extensive experimental results have been demonstrated in four benchmark iris databases namely: MMU1, UPOL, CASIA-Iris-distance, and UBIRIS.v2. The comparison with the state-of-the-art methods with respect to these databases shows the robustness and effectiveness of the proposed approach.