Personal identification based on handwriting

✍ Scribed by H.E.S. Said; T.N. Tan; K.D. Baker

• Book ID: 104160436
• Publisher: Elsevier Science
• Year: 2000
• Tongue: English
• Weight: 968 KB
• Volume: 33
• Category: Article
• ISSN: 0031-3203
• DOI: 10.1016/s0031-3203(99)00006-0

✦ Synopsis

Many techniques have been reported for handwriting-based writer identi"cation. The majority of techniques assume that the written text is "xed (e.g., in signature veri"cation). In this paper we attempt to eliminate this assumption by presenting a novel algorithm for automatic text-independent writer identi"cation. Given that the handwriting of di!erent people is often visually distinctive, we take a global approach based on texture analysis, where each writer's handwriting is regarded as a di!erent texture. In principle, this allows us to apply any standard texture recognition algorithm for the task (e.g., the multi-channel Gabor "ltering technique). Results of 96.0% accuracy on the classi"cation of 1000 test documents from 40 writers are very promising. The method is shown to be robust to noise and contents.