Human Interactive Proofs

Henry S. Baird; Daniel P. Lopresti; Amalia Rusu; Venu Govindaraju

Human Interactive Proofs

Henry S. Baird, Daniel P. Lopresti, Amalia Rusu, Venu Govindaraju

Fairfield University

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

Amalia Rusu (with Venu Govindaraju) is a contributing author, "Visual CAPTCHA with handwritten image analysis", pp. 42-52.

Chapter description:

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.

Original language	American English
Title of host publication	Human Interactive Proofs
State	Published - Jan 1 2005

Disciplines

Engineering

Cite this

@inbook{163a522efce9468ab9ae79181580165a,

title = "Human Interactive Proofs",

abstract = " Amalia Rusu (with Venu Govindaraju) is a contributing author, {"}Visual CAPTCHA with handwritten image analysis{"}, pp. 42-52. Chapter description: 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.",

author = "Baird, \{Henry S.\} and Lopresti, \{Daniel P.\} and Amalia Rusu and Venu Govindaraju",

year = "2005",

month = jan,

day = "1",

language = "American English",

booktitle = "Human Interactive Proofs",

}

TY - CHAP

T1 - Human Interactive Proofs

AU - Baird, Henry S.

AU - Lopresti, Daniel P.

AU - Rusu, Amalia

AU - Govindaraju, Venu

PY - 2005/1/1

Y1 - 2005/1/1

N2 - Amalia Rusu (with Venu Govindaraju) is a contributing author, "Visual CAPTCHA with handwritten image analysis", pp. 42-52. Chapter description: 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.

AB - Amalia Rusu (with Venu Govindaraju) is a contributing author, "Visual CAPTCHA with handwritten image analysis", pp. 42-52. Chapter description: 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.

UR - https://digitalcommons.fairfield.edu/engineering-books/16

M3 - Chapter

BT - Human Interactive Proofs

ER -

Human Interactive Proofs

Abstract

Disciplines

Other files and links

Cite this