Although the performance of current automatic recognition algorithms of on-line handwriting has much improved in recent years, there are still many problems with the actual application of these systems. It appears that the step from academical experiments to real-life use of such algorithms, in, e.g., portable pen computers, is still difficult. What is particularly intriguing is the fact that r...

Using handwritten characters we address two questions (i) what is the group identification performance of different alphabets (upper and lower case) and (ii) what are the best characters for the verification task (same writer/different writer discrimination) knowing demographic information about the writer such as age,sex or country of birth. The Bhattacharya distance is used to rank different ...

Writer identification and verification has been studied over the past decade due to the high demand of such implementations in a wide variety of offline handwritten data applications. Among the applications are verification of the identity of a person whom he or she claimed to be and forensic and historic document analysis in identifying the identity of the writer of the documents. This paper p...

In this paper a novel method for writer identification and retrieval is presented. Writer identification is the process of finding the author of a specific document by comparing it to documents in a database where writers are known, whereas retrieval is the task of finding similar handwritings or all documents of a specific writer. The method presented is using Convolutional Neural Networks (CN...

This paper introduces a novel method for online writer identification. Traditional methods make use of the distribution of directions in handwritten traces. The novelty of this paper comes from 1)We propose a text-independent writer identification that uses handwriting stroke’s probability distribution function (SPDF) as writer features; 2)We extract four dynamic features to characterize writer...