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Identication and Matching of Headstamp of Cartridge Using Iris Detection Algorithm
Blekinge Institute of Technology, Faculty of Engineering, Department of Applied Signal Processing.
Blekinge Institute of Technology, Faculty of Engineering, Department of Applied Signal Processing.
2016 (English)Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Identication of cartridge is very essential in the field of forensics, military or people who collect ammunitions. The cartridges can beidentied by their headstamps.This thesis presents work on identification and matching of cartridge headstamp from the image. The Libor Masek's open source iris recognition algorithm is considered for the identification of cartridge pattern from the image.The dataset is devoleped with the cartridge headstamp patterns and matching of cartridge headstamp patterns is implemented. For matching of the cartridge pattern the Hamming distance is considered as the metric to differentiate interclass and intraclass comparisons. Variance is used as a criteria to discard the unwanted areas of the cartridge headstamp pattern.Four distinct cartridge headstamp patterns are considered. Three cartridges of each headstamp pattern are considered for intra class comparisons. The validation of the method is performed.

Place, publisher, year, edition, pages
2016. , 38 p.
Keyword [en]
Cartridge headstamp, Cartridge headstamp matching, Cartridge pattern recognition, Iris recognition.
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:bth-13784OAI: oai:DiVA.org:bth-13784DiVA: diva2:1066096
Subject / course
ET2566 Master's Thesis (120 credits) in Electrical Engineering with emphasis on Signal processing
Educational program
ETASX Master of Science Programme in Electrical Engineering with emphasis on Signal Processing
Presentation
, Blekinge Institute of Technology
Supervisors
Examiners
Available from: 2017-01-18 Created: 2017-01-17 Last updated: 2017-01-18Bibliographically approved

Open Access in DiVA

BTH2016Yerragudi(4965 kB)68 downloads
File information
File name FULLTEXT02.pdfFile size 4965 kBChecksum SHA-512
8b2a065e510f06f12efafb55afc88b5a96c49e6d1e5c7203abadb9339f64f4c788570785c1bc931f0bddc27558cac760ee706d381f0452152895b512d7573e5b
Type fulltextMimetype application/pdf

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Department of Applied Signal Processing
Signal Processing

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Total: 68 downloads
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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf