For signature verification, there can be a large number of useful features including pen-speed, pen-pressure, etc. However, all these features may not be useful or even be harmful for a given person when not enough number of training samples are allowed. Namely, for an optimal verification, each person requires a different subset of all the possible features. Finding an optimal subset for an individual needs too much combinatorial efforts. Instead, we propose an approach using all the same features for every person by assigning a different weight to each feature according to the nature of the person's signature.
|Title of host publication||Proceedings of the 3rd International Conference on Document Analysis and Recognition, ICDAR 1995|
|Publisher||IEEE Computer Society|
|Number of pages||4|
|Publication status||Published - 1995|
|Event||3rd International Conference on Document Analysis and Recognition, ICDAR 1995 - Montreal, Canada|
Duration: 1995 Aug 14 → 1995 Aug 16
|Name||Proceedings of the International Conference on Document Analysis and Recognition, ICDAR|
|Conference||3rd International Conference on Document Analysis and Recognition, ICDAR 1995|
|Period||95/8/14 → 95/8/16|
Bibliographical notePublisher Copyright:
© 1995 IEEE.
All Science Journal Classification (ASJC) codes
- Computer Vision and Pattern Recognition