Age Sensitivity of Face Recognition Algorithms

This paper investigates the performance degradation of facial recognition systems due to the influence of age. A comparative analysis of verification performance is conducted for four subspace projection techniques combined with four different distance metrics. The experimental results based on a subset of the MORPH-II database show that the choice of subspace projection technique and associated distance metric can have a significant impact on the performance of the face recognition system for particular age groups

Note: Finger Imaging: A 21st Century Solution to Welfare Fraud at our Fingertips

This Note describes the finger imaging process and summarizes the current New York Social Services law regarding public assistance. It also outlines the current finger imaging bill before the New York State Legislature. Part III examines and considers the two major policy arguments against the implementation of the program. Part IV outlines the legal controversy regarding finger imaging and addresses each express concern as well as constitutional issues. Part V compares New York\u27s finger imaging legislation with similar legislation already in place in California and argues that the New York program will be as effective as California\u27s. In conclusion, this Note urges the New York State Legislature to enact a statewide finger imaging requirement for public assistance and embrace the finger imaging system as an effective and proper method of combatting welfare fraud in the state

Note: Finger Imaging: A 21st Century Solution to Welfare Fraud at our Fingertips

This Note describes the finger imaging process and summarizes the current New York Social Services law regarding public assistance. It also outlines the current finger imaging bill before the New York State Legislature. Part III examines and considers the two major policy arguments against the implementation of the program. Part IV outlines the legal controversy regarding finger imaging and addresses each express concern as well as constitutional issues. Part V compares New York\u27s finger imaging legislation with similar legislation already in place in California and argues that the New York program will be as effective as California\u27s. In conclusion, this Note urges the New York State Legislature to enact a statewide finger imaging requirement for public assistance and embrace the finger imaging system as an effective and proper method of combatting welfare fraud in the state

A Longitudinal Analysis on the Feasibility of Iris Recognition Performance for Infants 0-2 Years Old

The focus of this study was to longitudinally evaluate iris recognition for infants between the ages of 0 to 2 years old. Image quality metrics of infant and adult irises acquired on the same iris camera were compared. Matching performance was evaluated for four groups, infants 0 to 6 months, 7 to 12 months, 13 to 24 months, and adults. A mixed linear regression model was used to determine if infants’ genuine similarity scores changed over time. This study found that image quality metrics were different between infants and adults but in the older group, (13 to 24 months old) the image quality metric scores were more likely to be similar to adults. Infants 0 to 6 months old had worse performance at an FMR of 0.01% than infants 7 to 12 months, 13 to 24 months, and adults

Latent Print Examination and Human Factors: Improving the Practice Through a Systems Approach: The Report of the Expert Working Group on Human Factors in Latent Print Analysis

Fingerprints have provided a valuable method of personal identification in forensic science and criminal investigations for more than 100 years. Fingerprints left at crime scenes generally are latent prints—unintentional reproductions of the arrangement of ridges on the skin made by the transfer of materials (such as amino acids, proteins, polypeptides, and salts) to a surface. Palms and the soles of feet also have friction ridge skin that can leave latent prints. The examination of a latent print consists of a series of steps involving a comparison of the latent print to a known (or exemplar) print. Courts have accepted latent print evidence for the past century. However, several high-profile cases in the United States and abroad have highlighted the fact that human errors can occur, and litigation and expressions of concern over the evidentiary reliability of latent print examinations and other forensic identification procedures has increased in the last decade. “Human factors” issues can arise in any experience- and judgment-based analytical process such as latent print examination. Inadequate training, extraneous knowledge about the suspects in the case or other matters, poor judgment, health problems, limitations of vision, complex technology, and stress are but a few factors that can contribute to errors. A lack of standards or quality control, poor management, insufficient resources, and substandard working conditions constitute other potentially contributing factors

Biological fingerprint using scout computed tomographic images for positive patient identification

Purpose: Management of patient identification is an important issue that should be addressed to ensure patient safety while using modern healthcare systems. Patient identification errors can be mainly attributed to human errors or system problems. An error-tolerant system, such as a biometric system, should be able to prevent or mitigate potential misidentification occurrences. Herein, we propose the use of scout computed tomography (CT) images for biometric patient identity verification and present the quantitative accuracy outcomes of using this technique in a clinical setting. Methods: Scout CT images acquired from routine examinations of the chest, abdomen, and pelvis were used as biological fingerprints. We evaluated the resemblance of the follow-up with the baseline image by comparing the estimates of the image characteristics using local feature extraction and matching algorithms. The verification performance was evaluated according to the receiver operating characteristic (ROC) curves, area under the ROC curves (AUC), and equal error rates (EER). The closed-set identification performance was evaluated according to the cumulative match characteristic curves and rank-one identification rates (R1). Results: A total of 619 (383 males, 236 females, age range 21–92 years) patients who underwent baseline and follow-up chest–abdomen–pelvis CT scans on the same CT system were analyzed for verification and closed-set identification. The highest performances of AUC, EER, and R1 were 0.998, 1.22%, and 99.7%, respectively, in the considered evaluation range. Furthermore, to determine whether the performance decreased in the presence of metal artifacts, the patients were classified into two groups, namely scout images with (255 patients) and without (364 patients) metal artifacts, and the significance test was performed for two ROC curves using the unpaired Delong's test. No significant differences were found between the ROC performances in the presence and absence of metal artifacts when using a sufficient number of local features. Our proposed technique demonstrated that the performance was comparable to that of conventional biometrics methods when using chest, abdomen, and pelvis scout CT images. Thus, this method has the potential to discover inadequate patient information using the available chest, abdomen, and pelvis scout CT image; moreover, it can be applied widely to routine adult CT scans where no significant body structure effects due to illness or aging are present. Conclusions: Our proposed method can obtain accurate patient information available at the point-of-care and help healthcare providers verify whether a patient’s identity is matched accurately. We believe the method to be a key solution for patient misidentification problems.This is the peer reviewed version of the following article: Ueda, Y., Morishita, J. and Hongyo, T. (2019), Biological fingerprint using scout computed tomographic images for positive patient identification. Med. Phys., 46: 4600-4609, which has been published in final form at https://doi.org/10.1002/mp.13779. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibited

Facial soft biometrics for recognition in the wild: recent works, annotation and COTS evaluation

The role of soft biometrics to enhance person recognition systems in unconstrained scenarios has not been extensively studied. Here, we explore the utility of the following modalities: gender, ethnicity, age, glasses, beard and moustache. We consider two assumptions: i) manual estimation of soft biometrics, and ii) automatic estimation from two Commercial Off-The-Shelf systems (COTS). All experiments are reported using the LFW database. First, we study the discrimination capabilities of soft biometrics standalone. Then, experiments are carried out fusing soft biometrics with two state-of-the-art face recognition systems based on deep learning. We observe that soft biometrics is a valuable complement to the face modality in unconstrained scenarios, with relative improvements up to 40%=15% in the verification performance when using manual/automatic soft biometrics estimation. Results are reproducible as we make public our manual annotations and COTS outputs of soft biometrics over LFW, as well as the face recognition scoresThis work was funded by Spanish Guardia Civil and project CogniMetrics (TEC2015-70627-R) from MINECO/FEDE