TY - GEN
T1 - A human interactive proof algorithm using handwriting recognition
AU - Rusu, Amalia
AU - Govindaraju, Venu
PY - 2005
Y1 - 2005
N2 - The recognition of unconstrained handwriting continues to be a difficult task for computers despite active research for several decades. This is because handwritten text offers great challenges such as: character and word segmentation, character recognition, variation between handwriting styles, different character size and orientation, no font constraints, the type of printing surface, as well as the background clarity. In this paper we explore the gap in the ability in reading handwritten text between humans and computers to propose solutions for security problems in Web Services. We present a new HIP algorithm that uses handwriting recognition task to distinguish between humans and computers. We propose methods to deform handwritten text images to make them indecipherable by computers and explore the cognitive factors that assist humans in reading and understanding. Experimental results on both humans and computers are presented and compared.
AB - The recognition of unconstrained handwriting continues to be a difficult task for computers despite active research for several decades. This is because handwritten text offers great challenges such as: character and word segmentation, character recognition, variation between handwriting styles, different character size and orientation, no font constraints, the type of printing surface, as well as the background clarity. In this paper we explore the gap in the ability in reading handwritten text between humans and computers to propose solutions for security problems in Web Services. We present a new HIP algorithm that uses handwriting recognition task to distinguish between humans and computers. We propose methods to deform handwritten text images to make them indecipherable by computers and explore the cognitive factors that assist humans in reading and understanding. Experimental results on both humans and computers are presented and compared.
UR - https://www.scopus.com/pages/publications/33947364465
U2 - 10.1109/ICDAR.2005.18
DO - 10.1109/ICDAR.2005.18
M3 - Conference contribution
AN - SCOPUS:33947364465
SN - 0769524206
SN - 9780769524207
T3 - Proceedings of the International Conference on Document Analysis and Recognition, ICDAR
SP - 967
EP - 970
BT - Proceedings of the Eighth International Conference on Document Analysis and Recognition
T2 - 8th International Conference on Document Analysis and Recognition
Y2 - 31 August 2005 through 1 September 2005
ER -