首页|A bibliometric analysis of off-line handwritten document analysis literature (1990-2020)

A bibliometric analysis of off-line handwritten document analysis literature (1990-2020)

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  • NSTL
  • Elsevier
Providing computers with the ability to process handwriting is both important and challenging, since many difficulties (e.g., different writing styles, alphabets, languages, etc.) need to be overcome for ad -dressing a variety of problems (text recognition, signature verification, writer identification, word spot-ting, etc.). This paper reviews the growing literature on off-line handwritten document analysis over the last thirty years. A sample of 5389 articles is examined using bibliometric techniques. Using bibliomet-ric techniques, this paper identifies (i) the most influential articles in the area, (ii) the most productive authors and their collaboration networks, (iii) the countries and institutions that have led research on the topic, (iv) the journals and conferences that have published most papers, and (v) the most relevant research topics (and their related tasks and methodologies) and their evolution over the years. (c) 2021 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ )

Automatic document analysisOff-line handwriting recognitionWriter identificationSignature verificationBibliometricsScience mappingAUTOMATIC SIGNATURE VERIFICATIONSHAPE NORMALIZATION METHODSMACHINE-PRINTED TEXTCHARACTER-RECOGNITIONWRITER IDENTIFICATIONDIGIT RECOGNITIONWORD RECOGNITIONNEURAL-NETWORKSNUMERAL RECOGNITIONOFFLINE RECOGNITION

Ruiz-Parrado, Victoria、Heradio, Ruben、Aranda-Escolastico, Ernesto、Sanchez, Angel、Velez, Jose F.

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Univ Rey Juan Carlos URJC

Univ Nacl Educ Distancia UNED

2022

10.1016/j.patcog.2021.108513

Pattern Recognition

Pattern Recognition

EISCI
ISSN：0031-3203
年,卷(期)：2022.125
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