A Sigma-Lognormal Model for Handwritten Text CAPTCHA Generation

Author

Ramaiah, C. ; Plamondonm, R. ; Govindaraju, V.

Author_Institution

Univ. at Buffalo, Buffalo, NY, USA

fYear

2014

fDate

24-28 Aug. 2014

Firstpage

250

Lastpage

255

Abstract

Popular CAPTCHA systems consist of garbled printed text character images with significant distortions and noise. It is believed that humans have little difficulty in deciphering the text, whereas automated systems are foiled by the added noise and distortion. However, in recent years, several text based CAPTCHAs have been reported as broken, that is, automated systems can identify the text in the displayed image with a reasonable amount of success. An extension to the text based CAPTCHA concept is to utilize unconstrained handwritten text, which is still considered to be a challenging problem for automated systems. In this work, we present a automated handwritten CAPTCHA generation system by adding distortions to the Sigma-Lognormal representation of a handwritten word sample. In addition, several noise models are also considered. We perform experiments on the UNIPEN dataset and demonstrate the efficacy of the approach.

Keywords

distortion; handwritten character recognition; image representation; security of data; Completely Automated Public Turing test to tell Computers and Humans Apart; UNIPEN dataset; handwritten text CAPTCHA generation; handwritten word sample; noise models; sigma-lognormal model; sigma-lognormal representation; Accuracy; Additive noise; CAPTCHAs; Mathematical model; Speech recognition; Text recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition (ICPR), 2014 22nd International Conference on

Conference_Location

Stockholm

ISSN

1051-4651

Type

conf

DOI

10.1109/ICPR.2014.52

Filename

6976763