NDLI: Identity dominance: Using fingerprints to link an individual to a larger social structure

Content Provider	IEEE Xplore Digital Library
Author	Herdegen, D. Loew, M.H.
Copyright Year	2008
Description	Author affiliation: MITRE Corp., McLean, VA (Herdegen, D.) \|\| George Washington Univ., Washington, DC (Loew, M.H.)
Abstract	This is a fingerprint pattern and ridge count analysis for two population groups used to associate an individual to a group through qualitative and quantitative comparison. The fingerprint data from the two groups were analyzed using a classification and regression tree algorithm. Four distinct trees were produced. The first tree separated the two populations using only finger number and pattern. Subsequent trees separated the two populations using finger number, pattern, and ridge count. Including ridge counts increased the per-finger classification accuracy from 56.4% to 73.9% and 79.5% for right and left loop patterns respectively. Whorls with both ridge counts improved the classification accuracy to 83.3%. The classification accuracies provided the basis for determining the probability of correctly associating a person to one of the two groups. For each finger, the probability of correctly associating the finger to the group is binomially distributed based upon the classification probabilities. Association is based upon a majority vote. In the worst case with only finger pattern and finger number available, the expected probability of correctly associating the individual is 54.1% using all ten fingers. Adding ridge counts raises the lower bound to 90.8%. The upper bound using whorls with two ridge counts is 98.4%. Between these two extremes are cases in which the patterns vary among the fingers. Because the probability of correctly associating the individual to the city depends on the data available, cases where the fingerprint patterns or the deltas are not discernible reduce the probability of correct association accordingly.
Starting Page	1
Ending Page	4
File Size	349149
Page Count	4
File Format	PDF
ISBN	9781424431250
ISSN	15505219
DOI	10.1109/AIPR.2008.4906446
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-15
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fingerprint recognition Fingers Genetics Statistics Biometrics Pattern analysis Algorithm design and analysis Classification tree analysis Regression tree analysis Voting
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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