Standard

Arabic Manuscripts Identification Based on Feature Relation Graph. / Redkin, Oleg; Bernikova, Olga; Shalymov, Dmitry; Pavlov, Vladislav.

Proceedings of Artificial Intelligence and Natural Language and Information Extraction, Social Media and Web Search FRUCT Conference, AINL-ISMW FRUCT 2015. IEEE Canada, 2016. p. 83-88.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

Harvard

Redkin, O, Bernikova, O, Shalymov, D & Pavlov, V 2016, Arabic Manuscripts Identification Based on Feature Relation Graph. in Proceedings of Artificial Intelligence and Natural Language and Information Extraction, Social Media and Web Search FRUCT Conference, AINL-ISMW FRUCT 2015. IEEE Canada, pp. 83-88, Artificial Intelligence and Natural Language and Information Extraction, Social Media and Web Search FRUCT Conference (AINL-ISMW FRUCT 2015), St Petersburg, 8/11/15. <http://www.ainlfruct.com/>

APA

Redkin, O., Bernikova, O., Shalymov, D., & Pavlov, V. (2016). Arabic Manuscripts Identification Based on Feature Relation Graph. In Proceedings of Artificial Intelligence and Natural Language and Information Extraction, Social Media and Web Search FRUCT Conference, AINL-ISMW FRUCT 2015 (pp. 83-88). IEEE Canada. http://www.ainlfruct.com/

Vancouver

Redkin O, Bernikova O, Shalymov D, Pavlov V. Arabic Manuscripts Identification Based on Feature Relation Graph. In Proceedings of Artificial Intelligence and Natural Language and Information Extraction, Social Media and Web Search FRUCT Conference, AINL-ISMW FRUCT 2015. IEEE Canada. 2016. p. 83-88

Author

Redkin, Oleg ; Bernikova, Olga ; Shalymov, Dmitry ; Pavlov, Vladislav. / Arabic Manuscripts Identification Based on Feature Relation Graph. Proceedings of Artificial Intelligence and Natural Language and Information Extraction, Social Media and Web Search FRUCT Conference, AINL-ISMW FRUCT 2015. IEEE Canada, 2016. pp. 83-88

BibTeX

@inproceedings{3878249f182343f8b7833797b9d9ac97,
title = "Arabic Manuscripts Identification Based on Feature Relation Graph",
abstract = "We investigate a new metric based on the Feature Relation Graph (FRG). This metric has proved to be effective for the text independent Persian writer identification. Since Persian script is based on Arabic writing similar principles of analysis may be also applied to the Arabic manuscripts. We have investigated the FRG for Arabic handwritten texts. Pattern based features are extracted from handwritten texts using Gabor and XGabor filters. The extracted features are represented for each author based on the FRG that plays a role of a feature vector in the classification problems. We have also investigated different parameters of the FRG.",
author = "Oleg Redkin and Olga Bernikova and Dmitry Shalymov and Vladislav Pavlov",
year = "2016",
language = "Английский",
isbn = "978-952-68397-0-7",
pages = "83--88",
booktitle = "Proceedings of Artificial Intelligence and Natural Language and Information Extraction, Social Media and Web Search FRUCT Conference, AINL-ISMW FRUCT 2015",
publisher = "IEEE Canada",
address = "Канада",
note = "null ; Conference date: 08-11-2015 Through 13-11-2015",

}

RIS

TY - GEN

T1 - Arabic Manuscripts Identification Based on Feature Relation Graph

AU - Redkin, Oleg

AU - Bernikova, Olga

AU - Shalymov, Dmitry

AU - Pavlov, Vladislav

PY - 2016

Y1 - 2016

N2 - We investigate a new metric based on the Feature Relation Graph (FRG). This metric has proved to be effective for the text independent Persian writer identification. Since Persian script is based on Arabic writing similar principles of analysis may be also applied to the Arabic manuscripts. We have investigated the FRG for Arabic handwritten texts. Pattern based features are extracted from handwritten texts using Gabor and XGabor filters. The extracted features are represented for each author based on the FRG that plays a role of a feature vector in the classification problems. We have also investigated different parameters of the FRG.

AB - We investigate a new metric based on the Feature Relation Graph (FRG). This metric has proved to be effective for the text independent Persian writer identification. Since Persian script is based on Arabic writing similar principles of analysis may be also applied to the Arabic manuscripts. We have investigated the FRG for Arabic handwritten texts. Pattern based features are extracted from handwritten texts using Gabor and XGabor filters. The extracted features are represented for each author based on the FRG that plays a role of a feature vector in the classification problems. We have also investigated different parameters of the FRG.

M3 - статья в сборнике материалов конференции

SN - 978-952-68397-0-7

SP - 83

EP - 88

BT - Proceedings of Artificial Intelligence and Natural Language and Information Extraction, Social Media and Web Search FRUCT Conference, AINL-ISMW FRUCT 2015

PB - IEEE Canada

Y2 - 8 November 2015 through 13 November 2015

ER -

ID: 4747655