OcrV1, Main, Exploration, bibRecord, 001227

Visual CAPTCHA with Handwritten Image Analysis

Identifieur interne : 001227 ( Main/Exploration ); précédent : 001226; suivant : 001228

Visual CAPTCHA with Handwritten Image Analysis

Auteurs : Amalia Rusu [États-Unis] ; Venugopal Govindaraju [États-Unis]

Source :

Lecture Notes in Computer Science [ 0302-9743 ] ; 2005.

RBID : ISTEX:3B8ED9D0F5910D1B40ADC3E8981E90A6D0213977

Abstract

Abstract: By convention, CAPTCHA is an automated test that humans can pass but current computer programs can′t. In general, the research on CAPTCHA and Human Interactive Proofs is focusing on those recognition tasks that are harder for machines than for humans. The recognition of unconstrained handwriting continues to be a difficult task for computers and handwritten image analysis is still an unsolved problem. Therefore, handwriting recognition provides a reasonable gap between humans and machines that could be exploited and used for new CAPTCHA challenges. In this paper we use handwritten word images and explore Gestalt psychology to motivate our image transformations. The deformation methods are individually described and results are presented and compared to other traditional handwritten image transformations. Several applications for Web services would find our handwritten CAPTCHA an excellent biometric for online security and a way of defending online services against abusive attacks.

Url:

https://api.istex.fr/document/3B8ED9D0F5910D1B40ADC3E8981E90A6D0213977/fulltext/pdf

DOI: 10.1007/11427896_3

Affiliations:

Links toward previous steps (curation, corpus...)

to stream Istex, to step Corpus: 000C07
to stream Istex, to step Curation: 000B92
to stream Istex, to step Checkpoint: 000B36
to stream Main, to step Merge: 001263
to stream Main, to step Curation: 001227

Le document en format XML

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<front><div type="abstract" xml:lang="en">Abstract: By convention, CAPTCHA is an automated test that humans can pass but current computer programs can′t. In general, the research on CAPTCHA and Human Interactive Proofs is focusing on those recognition tasks that are harder for machines than for humans. The recognition of unconstrained handwriting continues to be a difficult task for computers and handwritten image analysis is still an unsolved problem. Therefore, handwriting recognition provides a reasonable gap between humans and machines that could be exploited and used for new CAPTCHA challenges. In this paper we use handwritten word images and explore Gestalt psychology to motivate our image transformations. The deformation methods are individually described and results are presented and compared to other traditional handwritten image transformations. Several applications for Web services would find our handwritten CAPTCHA an excellent biometric for online security and a way of defending online services against abusive attacks.</div>
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Visual CAPTCHA with Handwritten Image Analysis

Visual CAPTCHA with Handwritten Image Analysis

Source :

Abstract

Links toward previous steps (curation, corpus...)

Le document en format XML

Pour manipuler ce document sous Unix (Dilib)

Pour mettre un lien sur cette page dans le réseau Wicri