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NCJRS Celebrates National Library Week April 12-18

National Library Week

Started in 1958, National Library Week is a nationwide observance celebrated by all types of libraries - including the NCJRS Virtual Library. NCJRS invites you to explore the breadth and scope of the NCJRS Virtual Library collection and services. With more than 220,000 collection documents and 60,000 online resources, including all known Office of Justice Programs works, it is one of the world’s largest criminal justice special collections.

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NCJRS Abstract

The document referenced below is part of the NCJRS Library collection.
To conduct further searches of the collection, visit the NCJRS Abstracts Database.

How to Obtain Documents
NCJ Number: NCJ 241128     Find in a Library
Title: Improving Verification Accuracy by Synthesis of Locally Enhanced Biometric Images and Deformable Model
Author(s): Richa Singh ; Mayank Vatsa ; Afzel Noore
  Journal: Signal Processing  Volume:87  Issue:11  Dated:2007  Pages:2746 to 2764
Date Published: 2007
Page Count: 19
  Annotation: This article proposes a two-stage preprocessing framework that increases the verification performance of image-based biometric systems through image enhancement and deformation techniques.
Abstract: In biometrics, quality refers to the intrinsic physical data content, which pertains to the accuracy with which physical characteristics are represented in a given biometric data. The performance of a biometric system depends on the quality of images collected as either a reference or a live sample. This article proposes a SVM-based algorithm that selects good quality local regions from different globally enhanced images and synergistically combines them to produce a high-quality, feature-rich image. The algorithm can be used to remove multiple irregularities present locally in the image without affecting the good quality regions. The authors also propose the phase congruency-based deformation correction algorithm that deforms the query image with respect to the reference image in order to minimize any variations between the two images. The proposed framework can be applied with any of the recognition algorithms in order to improve the verification accuracy. Validation of the framework involved the selection of face and iris images as the two case studies. The preprocessing framework improved the verification performance of face and iris images by 7.6 percent and 1.6 percent, respectively. 4 tables, 20 figures, and 52 references
Main Term(s): Forensics/Forensic Sciences
Index Term(s): Testing and measurement ; Suspect identification ; Offender physical characteristics ; Investigative techniques ; Visual investigative analysis ; NIJ grant-related documents
Sponsoring Agency: National Institute of Justice (NIJ)
US Department of Justice
Office of Justice Programs
United States of America
Grant Number: 2003-RC-CX-K001
Type: Report (Study/Research)
Country: United States of America
Language: English
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