Handwriting Analysis: Applications in Person Identification and Forensic

Abstract

Handwriting is unique to each person, with distinctive features that help to identify and verify different characteristics of the individual. Handwriting analysis has been an area of research for many decades and attracted many researchers from diverse research disciplines, including graphology, psychology, paleography, neurology, forensics, and computer science. This chapter presents recent advances and various signal and image analysis techniques available for writer identification and gender detection from handwriting samples captured by online or offline devices. We discuss different steps commonly involved in person/gender identification systems in the literature, including pre-processing, feature extraction, and classification. Offline and online benchmark datasets used for experiments are further reviewed. This study provides a valuable source of information to students, researchers and practitioners who would like to start research in this field. It also provides future research directions to researchers to further expand research in the domains of person identification and gender detection.