Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Soft Computing
Published in: Soft Computing 3/2011

01-03-2011 | Focus

Method of verifying declared identity in optical answer sheets

Authors: Joseph A. Levi, Yosef A. Solewicz, Yael Dvir, Yisca Steinberg

Published in: Soft Computing | Issue 3/2011

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

In the use of optical answer sheet examinations, occasionally the identity of the examinee is in question. A novel method for characterizing the personal quality of mark shapes in optically read answer sheets is described. The method may be used to identify imposters in multiple choice examinations. All the marks are segmented and measured in multiple parameters including area, dimensions, perimeter and optical density. Imposter decisions are made on the collected data by comparing an identified test form against the form in question in comparison with a population using SVM (support vector machine) modeling. In testing the method, 300 test forms from 100 examinees from past tests were used. An EER (equal error rate) of 15–17% was found. While performance of the presented method is currently insufficient for practical purposes, future research options have been mentioned.
previous article Correlation-based classification of heartbeats for individual identification
next article Automatic video temporal segmentation based on multiple features

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now
Literature
Arazi B (1977) Handwriting identification by means of run-length measurements. IEEE Trans Syst Man Cybernet 7:878–881CrossRef
Bulacu M, Schomaker L (2003) Writer style from oriented edge fragments. Lecture notes in computer science, pp 460–469
Bulacu M, Schomaker L, Brink A (2007) Text-independent writer identification and verification using textural and allographic features. IEEE Trans Pattern Anal Mach Intell 29:701–717
Burges CJC (1998) A tutorial on support vector machines for pattern recognition. Data Mining Knowl Discov 2:1–47CrossRef
Cortes C, Vapnik V (1995) Support-vector networks. Mach Learn 20:273–297MATH
Franke K, Rose S (2004) Ink-deposition model: the relation of writing and ink deposition processes. In: Proceedings of the ninth international workshop on frontiers in handwriting recognition. IEEE Computer Society, Washington, DC, USA, pp 173–178
Gluhchev G, Thomas F (2005) Automatic slope evaluation of handwritten text. Int Confer Comput Syst Technol IIIA.10-1–IIIA.10-4
Hayes WL (1963) Statistics. Holt, Rinehart and Winston Inc., New York
Image Pro Plus [computer program] (2002) Version 4.5 for Windows. Media Cybernetics Inc., Bethesda
Joachims T (1999) Making large-scale SVM learning practical. In: Joachims T, Schölkopf B, Burges C, Smola A (eds) Advances in kernel methods: support vector learning. MIT Press, Cambridge
Kozinets BN et al (1967) Identification and differentiation of handwritings with the help of electronic computers (in Russian). Defense Technical Information Center
Maarse FJ, Schomaker LRB, Teulings HL (1988) Automatic identification of writers. In: Conference of the Dutch psychonomic Society on human–computer interaction: psychonomic aspects table of contents, Springer-Verlag New York, Inc. New York, pp 353–360
Martin A, Doddington G, Kamm T, Ordowski M, Przybocki M (1997) The DET curve in assessment of detection task performance. In: Proceedings of the 5th European conference on speech communication and technology: eurospeech; 1997 September 22–25; Rhodes, Greece, pp 1895–1898
Mikkilineni AK, Arslan O, Chiang PJ, Kumontoy RM, Allebach JP, Chiu GTC et al (2005) Printer forensics using SVM techniques. In: Proceedings of the IS&T’s NIP21: international conference on digital printing technologies; 2005 September 18–23, Baltimore, MD, pp 223–226
Niels R, Vuurpijl L, Schomaker L (2007) Automatic allograph matching in forensic writer identification. Int J Pattern Recognit Artif Intell 21:61–82CrossRef
Özgündüz E, Şentürk T, Karshgil ME (2005) Offline Signature Verification and Recognition by Support Vector Machine. In: European signal processing conference, EUSIPCO
Pervouchine V, Leedham G (2007) Extraction and analysis of forensic document examiner features used for writer identification. Pattern Recognit 40:1004–1013MATHCrossRef
Plamondon R et al (2000) Online and off-line handwriting recognition: a comprehensive survey. IEEE Trans Pattern Anal Mach Intell 22:63–84CrossRef
Schomaker L, Bulacu M, Franke K (2004) Automatic writer identification using fragmented connected-component contours. In: Frontiers in handwriting recognition, 2004. IWFHR-9 2004. Ninth international workshop on frontiers in handwriting recognition, pp 185–190
Slavík P, Govindaraju V (2000) An overview of run-length encoding of handwritten word images. Technical Report, Department of Computer Science, State University of New York at Buffalo
Vapnik VN (1995) The nature of statistical learning theory. Springer, New YorkMATH
Metadata
Title
Method of verifying declared identity in optical answer sheets
Authors
Joseph A. Levi
Yosef A. Solewicz
Yael Dvir
Yisca Steinberg
Publication date
01-03-2011
Publisher
Springer-Verlag
Published in
Soft Computing / Issue 3/2011
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-009-0526-x

Other articles of this Issue 3/2011

Soft Computing 3/2011 Go to the issue

Original Paper

An application of particle swarm optimization algorithm to clustering analysis

Focus

Automatic video temporal segmentation based on multiple features

Focus

2D face fitting-assisted 3D face reconstruction for pose-robust face recognition

Original Paper

Extension of the ELECTRE method based on interval-valued fuzzy sets

Original Paper

Hedges and successors in basic algebras

Original Paper

Hybrid differential evolution and Nelder–Mead algorithm with re-optimization

Premium Partner

    Image Credits