Human Identification Method Research Articles

Identification of Latent Lip Prints in Forensics - Review

Identification plays a major role in crime investigation. One of the most effective methods of identificationare fingerprints. Like fingerprints, lip prints are also unique for individuals and remain the same throughoutlife. They are not influenced by environmental changes, trauma and diseases. The uniqueness of lip has beenproven by researchers by using shape analysis and colour information. Lip prints can also provide someimportant information in crime investigations and have the ability to distinguish individuals and are usedin human identification purposes. Human lips recognition is one of the most emerging methods of humanidentification that originates from forensic and criminal practice. Lip prints are captured by police techniciansand further analysis provides valuable evidence. The use of lip prints first started in 1950 and researcheswere carried out in 1970. The wrinkles pattern on the lips has individual characteristics like fingerprints.Cheiloscopy is a forensic investigation method that deals with the study of elevations and depressions whichform a characteristic pattern on the external surface of the lips. This is unique for individuals. Lip printrecording is used in forensic investigation that deals with identification of humans, based on lip traces.Lip prints can be a basis for conclusion such as sexes, habits and character of that event. At a crime sitelip prints can either be visible or latent. Print produced by a traditional lipstick is easily identifiable. Latentprint investigation is important in resolving any criminal act. Latent lip prints are invisible prints and canbe identified by using fingerprint powder. Long lasting lipsticks produce prints that are invisible and requirereagents to develop the prints. The porous and multicoloured surfaces are the surfaces in which a print isdifficult to identify and cannot be easily seen. Cups, glasses, tissue papers and napkins may have imprintsof the suspect’s lips.

Morphological and dimensional assessment of the maxillary sinus for human identification and sexual dimorphism: A study using CBCT

Abstract The use of tomographic images for ante and post-mortem comparisons is a safe and useful method for human identification. Thus, the present study aimed to evaluate the reproducibility of the morphometric assessment of the maxillary sinus for human identification and investigate whether sexual dimorphism is present in a Brazilian population, using Cone Bean Computed Tomographic (CBCT) images. One hundred tomographic images were selected as sample. The exams were acquired using the iCAT Next Generation® CBCT machine. Two previously trained and calibrated examiners evaluated morphological and dimensional parameters of the maxillary sinus region in two different moments with a 15 days minimum interval between the evaluations. The evaluation was carried out on a 19-inch monitor and with iCAT Workstation Dental Imaging System software in a light-dimmed and quiet environment. Cohen's Kappa test analyzed categorical and discrete variables. Mann-Whitney-U-test and Student's t-test were used to analyze the differences between the mean values of dimensional parameters for males and females with a significance level of 5% (p

Transfer Learning Based Automatic Human Identification using Dental Traits- An Aid to Forensic Odontology

Forensic Odontology deals with identifying humans based on their dental traits because of their robust nature. Classical methods of human identification require more manual effort and are difficult to use for large number of Images. A Novel way of automating the process of human identification by using deep learning approaches is proposed in this paper. Transfer learning using AlexNet is applied in three stages: In the first stage, the features of the query tooth image are extracted and its location is identified as either in the upper or lower Jaw. In the second stage of transfer learning, the tooth is then classified into any of the four classes namely Molar, Premolar, Canine or Incisor. In the last stage, the classified tooth is then numbered according to the universal numbering system and finally the candidate identification is made by using distance as metrics. These three stage transfer learning approach proposed in this work helps in reducing the search space in the process of candidate matching. Also, instead of making the network classify all the 32 teeth into 32 different classes, this approach reduces the number of classes assigned to the classification layer in each stage thereby increasing the performance of the network. This work outperforms the classical approaches in terms of both accuracy and precision. The hit rate in human identification is also higher compared to the other state-of-art methods.

A comprehensive security analysis of match-in-database fingerprint biometric system

Abstract The match-in-database fingerprint biometric system has emerged as the most widely used human identification and authentication method in public and private sectors due to its high efficiency, low-cost, and ease of use. This paper provides an exhaustive insight into the security aspect of such systems. We propose a comprehensive threat model depicting sixteen vulnerable attack points, which can act as a reference model while designing a new biometric application. We provide a comparison between the existing and proposed threat model. This article pinpoints all probable attacks at each vulnerable location and suggests possible mitigation techniques to thwart such attack attempts. We investigate the attacks on such systems, present a threat model, and categorize them into eight classes while specifying the risk factor associated with each class. This facilitates any new attack on such a system to be classified into one of these eight classes.

A Novel Sparse Representation and Softmax Method for Human Activity Identification in Healthcare Systems

Human activity identification has been attracting extensive research attention due to its prominent applications in healthcare systems such as healthcare monitoring and rehabilitation process. Traditional methods are greatly dependent on hand-crafted feature extraction, hampering their generalization performance. In this research, a novel sparse representation and softmax (SRS) method is presented for human activity identification to reduce the computation complexity of the task and improve the accuracy of classification. The multi-class classifier based on the softmax function is firstly introduced to improve sensor data classification performance. Sparse representation technology is then applied in our work to extract human activity features from sensor data. The output of the classifier model, taking raw sensor data after transforming into a high-dimensional feature space as input, provides a normalization of the probability distribution of activity categories, thereby ensuring accuracy and efficiency under diverse human activities. Experiments on a collection of raw sensor data from wireless sensor networks demonstrate the identification accuracy of our approach compared with nearest neighbor, naive Bayesian classifier, and support vector machine methods. The F1-score of the proposed method is respectively 14.1%, 19.6%, and 6.8% higher than the approaches mentioned above, indicating the effectiveness of SRS.

Human Identification System Based on Spatial and Temporal Features in the Video Surveillance System

Human identification is the most significant topic in the bioinformatics field. Various human gait identification methods are available to identify humans, but detecting the objects based on the human gait is still a challenging task in the video surveillance system. Thus, an effective hybrid Bayesian approach is proposed for identifying the humans. The proposed hybrid Bayesian approach involves two stages as follows: the first stage is the human identification based on the object features, and the second stage is the human identification based on the spatial features. Initially, the videos are fed into the first stage, where the object detection is performed using the Viola Jones algorithm. Once the objects are detected, the feature extraction process is carried out by using a hierarchical skeleton to effectively extract the selective features. The object skeleton provides an effective and intuitive abstraction, which offers object recognition and object matching. The Bayesian network is adapted in the object-based features to identify humans. In the spatial-based human identification stage, only the spatial features are extracted and are passed into the gait-based Bayesian network to identify the humans. Finally, the resulted output is obtained using the fuzzy holoentropy for identifying the humans. The experimentation of the proposed hybrid Bayesian approach is performed using the dataset named UCF-Crime, and the performance is evaluated by considering the average value of the metrics, namely F1-score, precision, and recall which acquired 0.8820, 0.8770, and 0.9203, respectively.

The construction and application of a new 17-plex Y-STR system using universal fluorescent PCR.

Y-chromosomal short tandem repeat (Y-STR) polymorphisms are useful in forensic identification, population genetics, and human structures. However, the current Y-STR systems are limited in discriminating distant relatives in a family with a low discrimination power. Increasing the capacity of detecting Y chromosomal polymorphisms will drastically narrow down the matching number of genealogy populations or pedigrees. In this study, we developed a system containing 17 Y-STRs that are complementary to the current commercially available Y-STR kits. This system was constructed by multiplex PCR with expected sizes of 126-400bp labeled by different fluorescence molecules (DYS715, DYS709, DYS716, DYS713, and DYS607 labeled by FAM; DYS718, DYS723, DYS708, and DYS714 labeled by JOE; DYS712, DYS717, DYS721, and DYS605 labeled by TAMRA; and DYS719, DYS726, DYS598, and DYS722 labeled by ROX). The system was extensively tested for sensitivity, male specificity, species specificity, mixture, population genetics, and mutation rates following the Scientific Working Group on DNA Analysis Methods (SWGDAM) guidelines. The genetic data were obtained from eight populations with a total of 1260 individuals. Our results showed that all the 17 Y-STRs are human- and male-specific and include only one copy of the Y-chromosome. The 17 Y-STR system detects 143 alleles and has a high discrimination power (0.996031746). Mutation rates were different among the 17 Y-STRs, ranging from 0.30 to 3.03%. In conclusion, our study provides a robust, sensitive, and cost-effective genotyping method for human identification, which will be beneficial for narrowing the search scope when applied to genealogy searching with the Y-STR DNA databank.

Measurements of sex-related differences in maxillary sinus and mandibular canal characteristic using cone beam computed tomography

Abstract Background Methods for human identification, including sex determination, must enable the examination of severely burned, damaged, or decomposed bodies. Maxillofacial structures that can be used to determine sex include the maxillary sinus and mandibular canal. Cone beam computed tomography (CBCT) is a non-invasive, high-resolution method that can visualize maxillofacial anatomy, including the maxillary sinus and the mandibular canal. CBCT provides detailed measurements of any anatomical structure for forensic identification. Aim To evaluate the usefulness of a method to determine sex based on maxillary sinus size and mandibular canal position. Methods The height, length, and width of the maxillary sinus and the distances from the mandibular canal to the buccal, lingual, and inferior borders of the mandible were measured in 138 samples using Digital Image Communication in Medicine-compatible Carestream 3D Imaging Software©. Logistic regression analysis was performed to identify specific factors for sex determination. Results The size of the maxillary sinus and the distance from the mandibular canal to the inferior border of the mandible were significantly different between men and women (p Conclusion The height, length, and width of the maxillary sinus, as well as the distance from the mandibular canal to the inferior border of the mandible, can be utilized for sex determination via CBCT radiographic imaging.

Offline Handwritten Signature Recognition Based on SIFT and SURF Features Using SVMs

Biometric recognition for human identification plays a key role in the rapid development of computer vision and pattern recognition research areas. The biometrics, refers to the automatic identification of a person based behavioral characteristics, physiological properties or traits. Signature recognition is one such human identification method and can be performed either in offline or online mode. This paper proposed an offline handwritten signature recognition which is based on image processing technique, scale-invariant feature transform (SIFT) and speeded-up robust features (SURF) features and support vector machines (SVMs). The handwritten signature images were then recognized through the proposed method that involves identification of regions of interest and representation of those regions as SIFT or SURF, construction of codebooks and the multi-class classification of the feature histograms using support vector machines (SVMs). Experiments have been carried out with our dataset of 1600 samples and a recognition rate in excess of 95% was obtained over the ten-fold cross validations.

A study on a virtual simulation experiment with DNA in a biological evidence technology course during the COVID-19 pandemic

Biological evidence technology plays an important role in the field of crime scene investigation. DNA technology is known as one of the important ways to make a breakthrough in the resolution of a criminal case. Nonetheless, there are some problems in on-site experiment-based teaching during the COVID-2019 pandemic, which limits the students' incentives to acquire knowledge about DNA. Under these conditions, the goals and requirements of the Biological Evidence Technology course cannot be achieved. A virtual simulation experiment can solve these problems online. The students can gain a deeper understanding of the process and method of human DNA extraction and identification, and thus, the impact of experiment-based teaching improves. In this paper, we discuss the contents of DNA experiments, specifications of the simulation system, system requirements, the implementation process, and other parameters of the design. We investigated the early teaching effect. A virtual simulation experiment with DNA can overcome the limitations of devices (and other equipment) and spatial and temporal limitations during the COVID-2019 pandemic. Students can participate in the whole process of experiment-based teaching. Teaching mode “Internet + laboratory” increases the open access and sharing of experiment-based teaching resources.

Off-line Chinese Signature Verification Using Convolutional Neural Network

Background: The unique individual biological characteristics is used for identification in biometrics, which is safe and difficult to forge. Therefore, it can help to enhance the safety of access control system. Since the developing of modern information science and technology, computerbased signature verification system enables signature verification more efficiently and automatically in comparison with traditional human identification method. Methods: In order to improve the accuracy of Chinese signature verification, an off-line Chinese signature verification method based on deep convolutional neural network is proposed. First, the machine learning library Tensorflow is build, and the volunteers are invited to establish the offline Chinese signature dataset. Second, the dataset is pre-processed, including denoising, binarization and size normalization. Finally, three different CNN architectures (AlexNet, GoogleNet, VGGNet) are adopted to implement the signature verification. Results: Experimental results show that the performance of AlexNet is better than that of the other two convolutional neural network architectures, the accuracy of classification has been up to 99.77%, and verification rate is 87.5%. Conclusion: Compared with the traditional offline Chinese signature recognition method, the method based on the convolutional neural network Alex Net-f is better than other methods to some extent, and avoids the complicated feature engineering.

Forensic evaluation of VeriFiler™ Plus 6-dye chemistry kit composed of 23 loci with casework samples

STR markers have been the genetic markers of choice in forensic DNA analysis for the past twenty years, and has proven to be an extremely discriminating method for human identification in forensics. In this study, I have evaluated a six-dye STR multiplex assay composed of 23 autosomal STR loci, 1 insertion/deletion polymorphic marker on the Y chromosome, Amelogenin and two internal quality control markers (IQCS and IQCL). This Internal validation indicated that VeriFilerTM Plus PCR amplification kit was reproducible, sensitive, accurate and robust. Sensitivity testing showed that a full profile can be obtained even with 63pg of human DNA. Heterozygous allele balance varied between 99-60 % for samples with total DNA input ranging from 1 ng to 500pg. It is also suitable for mixture study. All the alleles of minor contributor were called for ratios of 1:1, 1:3 and 3:1. overall this study demonstrate that VeriFilerTM Plus PCR amplification kit is robust, reliable and suitable as an assay for human identification with forensic casework samples.

Development of a new 17 Y-STRs system using fluorescent-labelled universal primers and its application in Shanxi population in China

Y-chromosomal short tandem repeats (Y-STRs) polymorphisms are useful in forensic identification, population genetics and constructing of human structures. Increasing the number of Y-STRs and their polymorphism will drastically narrow down the matching number of genealogy populations or pedigrees when searching against a forensic DNA databank. In this study, we develop a system containing 17 complementary Y-STRs that are compatible and reinforce the current commercially available Y-STR kits. This system was constructed by multiplex PCR with expected size of 126bp-400bp using home-made universal primers labeled by different fluorescence (DYS715, DYS709, DYS716, DYS713, DYS607, DYS718, DYS723, DYS708, DYS714, DYS712, DYS717, DYS721, DYS605, DYS719, DYS726, DYS598 and DYS722). The genetic data were obtained from 394 individuals in Shanxi province, China. The Y-STR system has 131 haplotypes and high discrimination power is 1. In conclusion, our study provides a robust, sensitive and cost-effective genotyping method for human identification, which is beneficial for narrowing the searching scope when applying to the genealogy searching with Y-STR DNA databank.

Impact of DNA degradation on massively parallel sequencing-based autosomal STR, iiSNP, and mitochondrial DNA typing systems.

Biological samples, including skeletal remains exposed to environmental insults for extended periods of time, exhibit increasing levels of DNA damage and fragmentation. Human forensic identification methods typically use a combination of mitochondrial (mt) DNA sequencing and short tandem repeat (STR) analysis, which target segments of DNA ranging from 80 to 500base pairs (bps). Larger templates are often unavailable as skeletal samples age and the associated DNA degrades. Single-nucleotide polymorphism (SNP) loci target shorter templates and may serve as a solution to the problem. Recently developed assays for STR and SNP analysis using a massively parallel sequencing approach, such as the ForenSeq kit (Verogen, San Diego, CA), offer a means for generating results from degraded samples as they target templates down to 60 to 170bps. We performed a modeling study that demonstrates that SNPs can increase the significance of an identification when analyzing DNA down to an average size of 100bps for input amounts between 0.375 and 1ng of nuclear DNA. Observations from this study were then compared with human skeletal material results (n = 14, ninth to eighteenth centuries), which further demonstrated the utility of the ForenSeq kit for degraded samples. The robustness of the Promega PowerSeq™ Mito System was also tested with human skeletal remains (n = 70, ninth to eighteenth centuries), resulting in successful coverage of 99.29% of the mtDNA control region at 50× coverage or more. This was accompanied by modifications to a mainstream DNA extraction technique for skeletal remains that improved recovery of shorter templates.

Forensic Facial Approximation: Study of the Nose in Brazilian Subjects.

Forensic facial approximation is an auxiliary method for human identification and allows facial recognition. The midface, that includes the nose, is vital for the recognition of a familiar face. The purpose of this study was to set hard tissue parameters to estimate nasal width, to test the method to estimate nasal width of Brazilians, and to analyze the relationship between nasal profile and facial type. A total of 246 computed tomography scans (183 females and 63 males) of adults were analyzed in Horos. Bone tissue measurements and facial type classification were performed on the skull scan. Nasal profile morphology was accessed through the tool 3D surface rendering. There was a difference around 3mm from real to predicted nose through the method to estimate nasal width in Brazilians. So, the method may be used in forensic practice. Straight nose was associated with long face type.

Proteomic genotyping of fingermark donors with genetically variant peptides

Proteomic genotyping detects single amino acid polymorphisms to infer the genotype of corresponding non-synonymous SNPs. Like any DNA genotype, these inferences can be used to estimate random match probability. Fingermarks are a common source of biological evidence that is sample limited and a highly variable source of identifying DNA. Genetically variant peptides from fingermarks, that contain single amino acid polymorphisms, are an additional source of identifying genetic information. To discover these peptide biomarkers epidermal corneocytes from 9 subjects were isolated, processed, digested with trypsin and applied to mass spectrometry. The resulting proteomic and matching exome datasets were used to discover, characterize and validate 60 genetically variant peptides. An average of 28.8 ± 4.4 genetically variant peptides were detected from each subject resulting in a total of 264 SNP allele inferences with 260 true and 4 false positives, a false discovery rate of 1.5%. Random match probabilities were estimated using the genotype frequencies from the matching major populations in the 1000 Genomes Project. Estimates ranged up to a value of 1 in 1.7 × 108, with a median probability of 1 in 2.4 × 106. Furthermore, the proteomically-inferred genotypes are likely to be compatible with the STR-based random match probability estimates since the closest STR locus was 2.2 Mb from the nearest GVP-inferred SNP. This project represents a novel mode of genetic information that can be obtained from fingermarks and has the potential to complement other methods of human identification including analysis of ridge patterns or touch DNA.

ECG based human identification using Second Order Difference Plots

Background and objectiveECG is one of the biometric signals that has been studied in peer-reviewed over past years. The developments on the signal analysis methods show that the studies on the ECG would continue unabatedly. It has a common use on cardiac diseases with high rates of classification performances by integrating it with signal analysis methods. The aim of the study is to utilize the ECG for human identification. MethodsSecond Order Difference Plot (SODP) is a non-linear time-series analysis method that allows determining the features using the statistical analysis of the wave distributions. The SODP features were extracted using different quantification methods for ECG-based human identification. A new quantification approach has been proposed on the SODP for ECG-based human identification. The proposed method, Logarithmic Grid Analysis, was compared with the existing quantification methods on the SODP. The region of the SODP was divided into sub-regions with logarithmically increasing distances and the numbers of data points in each logarithmic sub regions were calculated in the proposed method. Three different databases were used to test the validity of the method. These records have been tested with the conventional feature extraction methods on the SODP. The long-term ECG signals were divided into 5-s short-term ECG signals. ResultsThe Logarithmic Grid Analysis features that were counted from short-time ECG signals were classified with k-Nearest Neighbor algorithm using 10-fold cross validation, and the identification performance of the proposed model was evaluated. Consequently, high accuracy rates of 91.96%, 99.86% and 95.12% were achieved on ECG-based human identification using the Logarithmic Grid Analysis method on the SODP. ConclusionsThe density score of data points at the center of the SODP is too high. This case increases the importance of the regions close the center in order to find the detailed and significant features from the SODP. The number of data points at the center has been extracted in more detail and the vertex areas of the major axes of the SODP can be interpreted in the aggregate sub-regions by using logarithmically increasing distances with a small number of feature size.

Daktyloskopia na przestrzeni wieków

Dactyloscopy as a method of human identification has, at the end of the second decade of the 21st century, an established, strong position, demonstrating itself in the whole range of tools available to law enforcement authorities to support investigations. Thanks to the development and popularization of modern biometric technologies, dactyloscopy is increasingly entering the sphere of non-police applications, used by millions of people every day, e.g. logging into electronic banking or unlocking access to smartphones with a finger. In many cultures, the interest in finger and hand skin ridges goes back thousands of years. Initially, it concerned an intentional creative process in the form of rock drawings, but with time, features were noticed in fingerprints that allow to distinguish and identify people. This process began in China more than two thousand years ago, while Europeans did not pay attention to fingerprints until the 17th century. However, it was not until the turn of the 19th and 20th centuries that a real revolution has begun, which changed the ability to verify human identity.

Statistical Approach for Subject’s State Identification by Face and Neck Thermograms with Small Training Sample

Existing methods of human psychophysiological states identification are either contact, or do not allow a test without the active involvement of a subject in this procedure. The use of thermal imaging systems has number of advantages: the lack of physical contact with the system, and the fact that temperature is a reliable indicator of health. In the work a new feature space consisting of 465 features divided into static (mean values in each face and neck area, correlation of temperatures between areas in each frame) and dynamic (ratio or correlation of temperatures between areas for subsequent frames) groups is proposed. The evaluation of the informativeness of the obtained features for psychophysiological state recognition is provided. The most informative features were found. Several classifiers were tested: a perceptron-type neural network, a network of quadratic forms, as well as a modified Bayes hypothesis formula, which showed the best result. The predicted probability of errors is less than 0.005.

Recovery of High Molecular Weight DNA from Old viscera Samples via Two Established Methods for Human Identification: A Comparative Study

At autopsy, in cases of suspected poisoning or drug intoxication, the viscera are mostly preserved in saturated common salt solution for toxicological analysis. However, frequent situation arises where the preserved viscera sample gets questioned for its source of origin and identification of the individual contributing the said viscera becomes important. In such a scenario, to identify the source of viscera, the DNA Profiling technique can be employed. This study aims at recovery of high molecular weight DNA suitable for DNA profiling from a 5-year-old viscera sample through modified validated methods. Approximately 2 g of viscera samples (kidney) were taken for the study and two different established DNA extraction methods were employed for isolating DNA for downstream procedures viz. quantitation of the extracted DNA, the amplification of the desired loci Polymerase chain reaction (PCR) and its subsequent genotyping. The yield of DNA extracted from both the methods was quantitated using real time PCR system and a complete DNA profile was obtained for the purpose of comparison with the biological relatives of the individual.