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Journal ArticleDOI

Review of: Strengthening Forensic Science in the United States: A Path Forward

01 Mar 2010-Journal of Forensic Sciences (Blackwell Publishing Ltd)-Vol. 55, Iss: 2, pp 560-564
About: This article is published in Journal of Forensic Sciences.The article was published on 2010-03-01. It has received 419 citations till now.
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Journal ArticleDOI
TL;DR: The experimental results indicate that singularity, ridge quality map, and ridge flow map are the most effective features in improving the matching accuracy.
Abstract: Latent fingerprint identification is of critical importance to law enforcement agencies in identifying suspects: Latent fingerprints are inadvertent impressions left by fingers on surfaces of objects. While tremendous progress has been made in plain and rolled fingerprint matching, latent fingerprint matching continues to be a difficult problem. Poor quality of ridge impressions, small finger area, and large nonlinear distortion are the main difficulties in latent fingerprint matching compared to plain or rolled fingerprint matching. We propose a system for matching latent fingerprints found at crime scenes to rolled fingerprints enrolled in law enforcement databases. In addition to minutiae, we also use extended features, including singularity, ridge quality map, ridge flow map, ridge wavelength map, and skeleton. We tested our system by matching 258 latents in the NIST SD27 database against a background database of 29,257 rolled fingerprints obtained by combining the NIST SD4, SD14, and SD27 databases. The minutiae-based baseline rank-1 identification rate of 34.9 percent was improved to 74 percent when extended features were used. In order to evaluate the relative importance of each extended feature, these features were incrementally used in the order of their cost in marking by latent experts. The experimental results indicate that singularity, ridge quality map, and ridge flow map are the most effective features in improving the matching accuracy.

292 citations


Cites background from "Review of: Strengthening Forensic S..."

  • ...Improving AFIS interoperability has been listed as one of the 13 recommendations by the NAS Committee on Identifying the Needs of the Forensic Science Community [23] to address the most important issues now facing the forensic science community....

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  • ...Improving AFIS interoperability has been listed as one of the thirteen recommendations by the NAS Committee on Identifying the Needs of the Forensic Science Community [21] to address the most important issues now facing forensic science community....

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Journal ArticleDOI
TL;DR: This study is the first large-scale study of the accuracy and reliability of latent print examiners’ decisions, in which 169 latentprint examiners each compared approximately 100 pairs of latent and exemplar fingerprints from a pool of 744 pairs.
Abstract: The interpretation of forensic fingerprint evidence relies on the expertise of latent print examiners. The National Research Council of the National Academies and the legal and forensic sciences communities have called for research to measure the accuracy and reliability of latent print examiners’ decisions, a challenging and complex problem in need of systematic analysis. Our research is focused on the development of empirical approaches to studying this problem. Here, we report on the first large-scale study of the accuracy and reliability of latent print examiners’ decisions, in which 169 latent print examiners each compared approximately 100 pairs of latent and exemplar fingerprints from a pool of 744 pairs. The fingerprints were selected to include a range of attributes and quality encountered in forensic casework, and to be comparable to searches of an automated fingerprint identification system containing more than 58 million subjects. This study evaluated examiners on key decision points in the fingerprint examination process; procedures used operationally include additional safeguards designed to minimize errors. Five examiners made false positive errors for an overall false positive rate of 0.1%. Eighty-five percent of examiners made at least one false negative error for an overall false negative rate of 7.5%. Independent examination of the same comparisons by different participants (analogous to blind verification) was found to detect all false positive errors and the majority of false negative errors in this study. Examiners frequently differed on whether fingerprints were suitable for reaching a conclusion.

282 citations

Journal ArticleDOI
TL;DR: Experimental results show that the use of soft biometric traits is able to improve the face-recognition performance of a state-of-the-art commercial matcher.
Abstract: Soft biometric traits embedded in a face (e.g., gender and facial marks) are ancillary information and are not fully distinctive by themselves in face-recognition tasks. However, this information can be explicitly combined with face matching score to improve the overall face-recognition accuracy. Moreover, in certain application domains, e.g., visual surveillance, where a face image is occluded or is captured in off-frontal pose, soft biometric traits can provide even more valuable information for face matching or retrieval. Facial marks can also be useful to differentiate identical twins whose global facial appearances are very similar. The similarities found from soft biometrics can also be useful as a source of evidence in courts of law because they are more descriptive than the numerical matching scores generated by a traditional face matcher. We propose to utilize demographic information (e.g., gender and ethnicity) and facial marks (e.g., scars, moles, and freckles) for improving face image matching and retrieval performance. An automatic facial mark detection method has been developed that uses (1) the active appearance model for locating primary facial features (e.g., eyes, nose, and mouth), (2) the Laplacian-of-Gaussian blob detection, and (3) morphological operators. Experimental results based on the FERET database (426 images of 213 subjects) and two mugshot databases from the forensic domain (1225 images of 671 subjects and 10 000 images of 10 000 subjects, respectively) show that the use of soft biometric traits is able to improve the face-recognition performance of a state-of-the-art commercial matcher.

239 citations


Cites background from "Review of: Strengthening Forensic S..."

  • ...The proposed work is an effort towards establishing the scientific basis and capability of quantitative analysis to exploit the NGI activity [37]....

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Journal ArticleDOI
TL;DR: In a comprehensive comparison of face identification by humans and computers, it is found that forensic facial examiners, facial reviewers, and superrecognizers were more accurate than fingerprint examiners and students on a challenging face identification test.
Abstract: Achieving the upper limits of face identification accuracy in forensic applications can minimize errors that have profound social and personal consequences. Although forensic examiners identify faces in these applications, systematic tests of their accuracy are rare. How can we achieve the most accurate face identification: using people and/or machines working alone or in collaboration? In a comprehensive comparison of face identification by humans and computers, we found that forensic facial examiners, facial reviewers, and superrecognizers were more accurate than fingerprint examiners and students on a challenging face identification test. Individual performance on the test varied widely. On the same test, four deep convolutional neural networks (DCNNs), developed between 2015 and 2017, identified faces within the range of human accuracy. Accuracy of the algorithms increased steadily over time, with the most recent DCNN scoring above the median of the forensic facial examiners. Using crowd-sourcing methods, we fused the judgments of multiple forensic facial examiners by averaging their rating-based identity judgments. Accuracy was substantially better for fused judgments than for individuals working alone. Fusion also served to stabilize performance, boosting the scores of lower-performing individuals and decreasing variability. Single forensic facial examiners fused with the best algorithm were more accurate than the combination of two examiners. Therefore, collaboration among humans and between humans and machines offers tangible benefits to face identification accuracy in important applications. These results offer an evidence-based roadmap for achieving the most accurate face identification possible.

229 citations

Journal ArticleDOI
TL;DR: The results provide strong evidence of an allegiance effect among some forensic experts in adversarial legal proceedings.
Abstract: How objective are forensic experts when they are retained by one of the opposing sides in an adversarial legal proceeding? Despite long-standing concerns from within the legal system, little is known about whether experts can provide opinions unbiased by the side that retained them. In this experiment, we paid 108 forensic psychologists and psychiatrists to review the same offender case files, but deceived some to believe that they were consulting for the defense and some to believe that they were consulting for the prosecution. Participants scored each offender on two commonly used, well-researched risk-assessment instruments. Those who believed they were working for the prosecution tended to assign higher risk scores to offenders, whereas those who believed they were working for the defense tended to assign lower risk scores to the same offenders; the effect sizes (d) ranged up to 0.85. The results provide strong evidence of an allegiance effect among some forensic experts in adversarial legal proceedings.

204 citations