The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Propomos um método de extração de características pessoais baseado em informações de caligrafia on-line. A pesquisa mais recente tem se concentrado na verificação de assinaturas, especialmente na área de verificação on-line de redatores. No entanto, a verificação de assinaturas tem um sério problema, pois aceita caligrafia falsa. Para resolver este problema, introduzimos um método de verificação de gravador on-line que utiliza caracteres comuns. Neste método, quaisquer caracteres manuscritos (ou seja, caracteres comuns) são aceitos como texto no processo de verificação, e o texto usado no processo de verificação pode ser diferente daquele usado no processo de inscrição. No entanto, no método proposto, as características pessoais são extraídas apenas da forma dos traços, e ainda é incerto quão eficientes outras informações on-line, como a pressão da escrita ou a inclinação da caneta, são para extrair características pessoais. Portanto, propomos um método de extração de características pessoais baseado em informações de caligrafia on-line, incluindo informações sobre pressão de escrita e inclinação da caneta. No método proposto, as informações de caligrafia são descritas por um conjunto de curvas tridimensionais, e as características pessoais são descritas por um conjunto de descritores de Fourier para as curvas tridimensionais. Também discutimos a confiabilidade do método proposto com alguns resultados de simulação usando dados manuscritos. A partir desses resultados de simulação, fica claro que o método proposto extrai efetivamente características pessoais de personagens comuns.
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Yasushi YAMAZAKI, Naohisa KOMATSU, "Extraction of Personal Features from On-Line Handwriting Information in Context-Independent Characters" in IEICE TRANSACTIONS on Fundamentals,
vol. E83-A, no. 10, pp. 1955-1962, October 2000, doi: .
Abstract: We propose an extraction method of personal features based on on-line handwriting information. Most recent research has been focused on signature verification, especially in the field of on-line writer verification. However, signature verification has a serious problem in that it will accept forged handwriting. To solve this problem, we have introduced an on-line writer verification method which uses ordinary characters. In this method, any handwritten characters (i.e., ordinary characters) are accepted as a text in the verification process, and the text used in the verification process can be different from that in the enrollment process. However, in the proposed method, personal features are extracted only from the shape of strokes, and it is still uncertain how efficient other on-line information, such as writing pressure or pen inclination, is for extracting personal features. Therefore, we propose an extraction method of personal features based on on-line handwriting information, including writing-pressure and pen-inclination information. In the proposed method, handwriting information is described by a set of three-dimensional curves, and personal features are described by a set of Fourier descriptors for the three-dimensional curves. We also discuss the reliability of the proposed method with some simulation results using handwritten data. From these simulation results, it is clear that the proposed method effectively extracts personal features from ordinary characters.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e83-a_10_1955/_p
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@ARTICLE{e83-a_10_1955,
author={Yasushi YAMAZAKI, Naohisa KOMATSU, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Extraction of Personal Features from On-Line Handwriting Information in Context-Independent Characters},
year={2000},
volume={E83-A},
number={10},
pages={1955-1962},
abstract={We propose an extraction method of personal features based on on-line handwriting information. Most recent research has been focused on signature verification, especially in the field of on-line writer verification. However, signature verification has a serious problem in that it will accept forged handwriting. To solve this problem, we have introduced an on-line writer verification method which uses ordinary characters. In this method, any handwritten characters (i.e., ordinary characters) are accepted as a text in the verification process, and the text used in the verification process can be different from that in the enrollment process. However, in the proposed method, personal features are extracted only from the shape of strokes, and it is still uncertain how efficient other on-line information, such as writing pressure or pen inclination, is for extracting personal features. Therefore, we propose an extraction method of personal features based on on-line handwriting information, including writing-pressure and pen-inclination information. In the proposed method, handwriting information is described by a set of three-dimensional curves, and personal features are described by a set of Fourier descriptors for the three-dimensional curves. We also discuss the reliability of the proposed method with some simulation results using handwritten data. From these simulation results, it is clear that the proposed method effectively extracts personal features from ordinary characters.},
keywords={},
doi={},
ISSN={},
month={October},}
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TY - JOUR
TI - Extraction of Personal Features from On-Line Handwriting Information in Context-Independent Characters
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1955
EP - 1962
AU - Yasushi YAMAZAKI
AU - Naohisa KOMATSU
PY - 2000
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E83-A
IS - 10
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - October 2000
AB - We propose an extraction method of personal features based on on-line handwriting information. Most recent research has been focused on signature verification, especially in the field of on-line writer verification. However, signature verification has a serious problem in that it will accept forged handwriting. To solve this problem, we have introduced an on-line writer verification method which uses ordinary characters. In this method, any handwritten characters (i.e., ordinary characters) are accepted as a text in the verification process, and the text used in the verification process can be different from that in the enrollment process. However, in the proposed method, personal features are extracted only from the shape of strokes, and it is still uncertain how efficient other on-line information, such as writing pressure or pen inclination, is for extracting personal features. Therefore, we propose an extraction method of personal features based on on-line handwriting information, including writing-pressure and pen-inclination information. In the proposed method, handwriting information is described by a set of three-dimensional curves, and personal features are described by a set of Fourier descriptors for the three-dimensional curves. We also discuss the reliability of the proposed method with some simulation results using handwritten data. From these simulation results, it is clear that the proposed method effectively extracts personal features from ordinary characters.
ER -