Online and off-line handwriting recognition: a comprehensive survey

R. Plamondon, S.N. Srihari
<span title="">2000</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="" style="color: black;">IEEE Transactions on Pattern Analysis and Machine Intelligence</a> </i> &nbsp;
AbstractÐHandwriting 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
more &raquo; ... ectronic data, and the basic concepts behind written language recognition algorithms. Both the on-line 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. acceptance by K. Bowyer. For information on obtaining reprints of this article, please send e-mail to:, and reference IEEECS Log Number 110293. 0162-8828/00/$10.00 ß 2000 IEEE Fig. 1. (a) Off-line word. The image of the word is converted into gray-level pixels using a scanner. (b) On-line word. The xY y coordinates of the pentip are recorded as a function of time with a digitizer.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="">doi:10.1109/34.824821</a> <a target="_blank" rel="external noopener" href="">fatcat:d2pq2n2yhra65cq2h7zzllhctm</a> </span>
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