TY - GEN
T1 - Gender identification through handwriting
T2 - 11th IEEE International Conference on Cognitive Infocommunications, CogInfoCom 2020
AU - Cordasco, Gennaro
AU - Buonanno, Michele
AU - Faundez-Zanuy, Marcos
AU - Riviello, Maria Teresa
AU - Likforman-Sulem, Laurence
AU - Esposito, Anna
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/9/23
Y1 - 2020/9/23
N2 - The present study was designed to identify writer's gender trough online handwriting and drawing analysis. Two groups - one of 126 males (mean age 24.65, SD=2.45) and the other of 114 females (mean age 24.51, SD=2.50) participants were recruited in the experiment. They were asked to perform seven writing and drawing tasks utilizing a digitizing tablet and a special writing device. Seventeen writing features grouped into five categories have been considered. The experiment's results show that the set of considered features enable to discriminate between male and female writers investigating their performance while copying a house drawing (task 2), writing words in capital letters (task 3) and writing a complete sentence in cursive letters (task 7), in particular focusing on Ductus (number of strokes) and Time categories of writing features.
AB - The present study was designed to identify writer's gender trough online handwriting and drawing analysis. Two groups - one of 126 males (mean age 24.65, SD=2.45) and the other of 114 females (mean age 24.51, SD=2.50) participants were recruited in the experiment. They were asked to perform seven writing and drawing tasks utilizing a digitizing tablet and a special writing device. Seventeen writing features grouped into five categories have been considered. The experiment's results show that the set of considered features enable to discriminate between male and female writers investigating their performance while copying a house drawing (task 2), writing words in capital letters (task 3) and writing a complete sentence in cursive letters (task 7), in particular focusing on Ductus (number of strokes) and Time categories of writing features.
KW - Drawing
KW - Gender recognition
KW - Handwriting
KW - Online analysis
U2 - 10.1109/CogInfoCom50765.2020.9237863
DO - 10.1109/CogInfoCom50765.2020.9237863
M3 - Conference contribution
AN - SCOPUS:85096357531
T3 - 11th IEEE International Conference on Cognitive Infocommunications, CogInfoCom 2020 - Proceedings
SP - 197
EP - 202
BT - 11th IEEE International Conference on Cognitive Infocommunications, CogInfoCom 2020 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 23 September 2020 through 25 September 2020
ER -