Browsing by Subject "Biometric identification"

Now showing 1 - 4 of 4
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    3D facial phenotyping by biometric sibling matching used in contemporary genomic methodologies
    (Public Library of Science, 2021-05-13) Hoskens, Hanne; Liu, Dongjing; Naqvi, Sahin; Lee, Myoung Keun; Eller, Ryan J.; Indencleef, Karlijne; White, Julie D.; Li, Jiarui; Larmuseau, Maarten H. D.; Hens, Greet; Wysocka, Joanna; Walsh, Susan; Richmond, Stephen; Shriver, Mark D.; Shaffer, John R.; Peeters, Hilde; Weinberg, Seth M.; Claes, Peter; Biology, School of Science
    The analysis of contemporary genomic data typically operates on one-dimensional phenotypic measurements (e.g. standing height). Here we report on a data-driven, family-informed strategy to facial phenotyping that searches for biologically relevant traits and reduces multivariate 3D facial shape variability into amendable univariate measurements, while preserving its structurally complex nature. We performed a biometric identification of siblings in a sample of 424 children, defining 1,048 sib-shared facial traits. Subsequent quantification and analyses in an independent European cohort (n = 8,246) demonstrated significant heritability for a subset of traits (0.17-0.53) and highlighted 218 genome-wide significant loci (38 also study-wide) associated with facial variation shared by siblings. These loci showed preferential enrichment for active chromatin marks in cranial neural crest cells and embryonic craniofacial tissues and several regions harbor putative craniofacial genes, thereby enhancing our knowledge on the genetic architecture of normal-range facial variation.
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    A Multi-stage Non-cooperative Iris Recognition Approach with Enhanced Template Security
    (2011) Yang, Kai; Du, Eliza Yingzi; Chen, Yaobin; Zheng, Jiangyu; Zou, Xukai
    Biometrics identi es/veri es a person using his/her physiological or behavioral characteristics. It is becoming an important ally for law enforcement and homeland security. Among all the biometric modalities, iris is tested to be the most accurate one. However, most existing methods are not designed for non-cooperative users and cannot work with o -angle or low quality iris images. In this thesis, we propose a robust multi-stage feature extraction and matching approach for non-cooperative iris recognition. We developed the SURF-like method to extract stable feature points, used Gabor Descriptor method for local feature description, and designed the multi- stage feature extraction and matching scheme to improve the recognition accuracy and speed. The related experimental results show that the proposed method is very promising. In addition, two template security enhanced schemes for the proposed non- cooperative iris recognition are introduced. The related experimental results show that these two schemes can e ectively realize cancelability of the enrolled biometric templates while at the same time achieving high accuracy.
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    A NEW APPROACH FOR HUMAN IDENTIFICATION USING THE EYE
    (2010) Thomas, N. Luke; Du, Yingzi; Rizkalla, Maher; King, Brian
    The vein structure in the sclera, the white and opaque outer protective covering of the eye, is anecdotally stable over time and unique to each person. As a result, it is well suited for use as a biometric for human identification. A few researchers have performed sclera vein pattern recognition and have reported promising, but low accuracy, initial results. Sclera recognition poses several challenges: the vein structure moves and deforms with the movement of the eye and its surrounding tissues; images of sclera patterns are often defocused and/or saturated; and, most importantly, the vein structure in the sclera is multi-layered and has complex non-linear deformation. The previous approaches in sclera recognition have treated the sclera patterns as a one-layered vein structure, and, as a result, their sclera recognition accuracy is not high. In this thesis, we propose a new method for sclera recognition with the following contributions: First, we developed a color-based sclera region estimation scheme for sclera segmentation. Second, we designed a Gabor wavelet based sclera pattern enhancement method, and an adaptive thresholding method to emphasize and binarize the sclera vein patterns. Third, we proposed a line descriptor based feature extraction, registration, and matching method that is scale-, orientation-, and deformation-invariant, and can mitigate the multi-layered deformation effects and tolerate segmentation error. It is empirically verified using the UBIRIS and IUPUI multi-wavelength databases that the proposed method can perform accurate sclera recognition. In addition, the recognition results are compared to iris recognition algorithms, with very comparable results.
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    Preparing a collection of radiology examinations for distribution and retrieval
    (Oxford University Press, 2016-03) Demner-Fushman, Dina; Kohli, Marc D.; Rosenman, Marc B.; Shooshan, Sonya E.; Rodriguez, Laritza; Antani, Sameer; Thoma, George R.; McDonald, Clement J.; Department of Radiology and Imaging Sciences, IU School of Medicine
    OBJECTIVE: Clinical documents made available for secondary use play an increasingly important role in discovery of clinical knowledge, development of research methods, and education. An important step in facilitating secondary use of clinical document collections is easy access to descriptions and samples that represent the content of the collections. This paper presents an approach to developing a collection of radiology examinations, including both the images and radiologist narrative reports, and making them publicly available in a searchable database. MATERIALS AND METHODS: The authors collected 3996 radiology reports from the Indiana Network for Patient Care and 8121 associated images from the hospitals' picture archiving systems. The images and reports were de-identified automatically and then the automatic de-identification was manually verified. The authors coded the key findings of the reports and empirically assessed the benefits of manual coding on retrieval. RESULTS: The automatic de-identification of the narrative was aggressive and achieved 100% precision at the cost of rendering a few findings uninterpretable. Automatic de-identification of images was not quite as perfect. Images for two of 3996 patients (0.05%) showed protected health information. Manual encoding of findings improved retrieval precision. CONCLUSION: Stringent de-identification methods can remove all identifiers from text radiology reports. DICOM de-identification of images does not remove all identifying information and needs special attention to images scanned from film. Adding manual coding to the radiologist narrative reports significantly improved relevancy of the retrieved clinical documents. The de-identified Indiana chest X-ray collection is available for searching and downloading from the National Library of Medicine (http://openi.nlm.nih.gov/).