Online and off-line handwriting recognition: a comprehensive survey

TLDR

Handwriting remains a ubiquitous communication medium, and its machine recognition is practically important for tasks such as reading notes, postal addresses, bank checks, and form fields. This survey aims to describe handwritten language, its conversion to electronic data, and the fundamental concepts of recognition algorithms. The review covers online recognition using trajectory data, offline recognition from scanned images, preprocessing, character and word recognition, system performance, and related applications such as signature verification and writer authentication.

Abstract

Handwriting has continued to persist as a means of communication and recording information in day-to-day life even with the introduction of new technologies. Given its ubiquity in human transactions, machine recognition of handwriting has practical significance, as in reading handwritten notes in a PDA, in postal addresses on envelopes, in amounts in bank checks, in handwritten fields in forms, etc. This overview describes the nature of handwritten language, how it is transduced into electronic data, and the basic concepts behind written language recognition algorithms. Both the online case (which pertains to the availability of trajectory data during writing) and the off-line case (which pertains to scanned images) are considered. Algorithms for preprocessing, character and word recognition, and performance with practical systems are indicated. Other fields of application, like signature verification, writer authentification, handwriting learning tools are also considered.