Automatic Writer Identification and Verification using Online Handwriting

 Sachin Gupta (homepage)

Automatic person identification is one of the major concerns in this era of automation. However, this is not a new problem and our society has adopted several different ways to authenticate the identity of a person such as signature and possessing a document. With the advent of electronic communication media (Internet), the interactions are becoming more and more automatic and thus the problem of identity theft has became even more severe. Even, the traditional modes of person authentication systems such as Possessions and Knowledge are not able to solve this problem. Possessions include physical possessions such as keys, passports, and smart cards. Knowledge is a piece of information that is memorized, such as a password and is supposed to be kept a secret. Knowledge and possession based methods are more focused on "what you know" or "what you possess" rather than "who you are". Due to inability of knowledge and possession based authentication methods to handle the security concerns, biometrics research have gained significant momentum in the last decade as the security concerns are increasing due to increasing automation of every field. Biometrics refers to authentication of a person using a physiological and behavioral trait of the individual that distinguish him from others. Biometric authentication has various advantages over knowledge and possession based identification methods including ease of use and non repudiation. In this thesis, we address the problem of handwriting biometrics. Handwriting is a behavioral biometric as it is generated as the consequence of an action performed by a person. Handwriting identification also has a long history. Signature (a specific instance of handwriting) has been used for authentication of legal documents for a long time.

This thesis addresses the various problems related to automatic handwriting identification. Most of the writer identification work is being done manually till date as a lot of context dependent information, such as, source of documents, nature of handwriting, etc. is difficult to model mathematically. However, they can be easily analyzed by human experts. Still, an automatic handwriting analysis system is useful as it can remove subjectivity from the process of handwriting identification and can be used for expert advice in various court cases. The final aim of this research is to design efficient algorithms for automatic feature extraction and recognition of the writer from a given handwritten document with as less human intervention as possible.

Specifically, we propose efficient solutions to three different applications of handwriting identification. First we look at the problem of determining the authorship of an arbitrary piece of online handwritten text. We then analyze the discriminative information from online handwriting to propose an efficient and accurate approach for text-dependent writer verification for practical and low security applications. We also look at the problem of repudiation in handwritten documents for forensic document examination. After introducing the problem of repudiation in handwritten documents, we propose an algorithm for repudiation detection in the handwritten documents. Handwriting identification is quite different from handwriting recognition; the other popular sub-field of automatic handwriting analysis. Handwriting recognition tries to identify the content of a handwritten text and tries to minimize variations due to writing style. On the other hand, in the case of handwriting identification, variations due to style is sought out.

Related Publications

• Sachin Gupta and Anoop M. Namboodiri  - Text-Dependent Writer Verification Using Boosting Proceedings of International Conference of Frontiers in Handwriting Recognition, Montreal, Canada, 2008 [PDF]
  

• Sachin Gupta and Anoop M. Namboodiri - Repudiation Detection in Handwritten Documents Proc of The 2nd International Conference on Biometics (ICB'07), PP. 356-365 Seoul, Korea, 27-29 August, 2007. [PDF]
  

• Anoop M. Namboodiri and Sachin Gupta - Text Independent Writer Identification from Online Handwriting, International Workshop on Frontiers in Handwriting Recognition(IWFHR'06), October 23-26, 2006, La Baule, Centre de Congreee Atlantia, France. [PDF]
  

Downloads