Offline writer verification based on Bangla handwritten characters using enhanced textual feature
Paul, Jaya ; Sarkar, Anasua LU
; Halder, Chayan
and Roy, Kaushik
(2017)
p.1-22
- Abstract
This chapter proposes a novel offline text dependent writer verification method based on Gray Level Co-occurrence Matrix (GLCM). The method is used to combine the result of Dual Tree Complex Wavelet Transforms (DT-CWT) and GLCM features to enhance the GLCM feature performance. The texture is a very important characteristic, which is used to verify the known writer from unknown writers. We have used 615 documents from 123 writers producing 43665 numbers of Bangla Isolated characters. The results show that these selected texture features have high distinction accuracy and hence is appropriate for efficient use in the challenging task of automatic writer verification.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/6eea2b86-e8a8-4d44-bf17-9965e8a68638
- author
- Paul, Jaya
; Sarkar, Anasua
LU
; Halder, Chayan
and Roy, Kaushik
- publishing date
- 2017-01-01
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- host publication
- Hybrid Intelligent Techniques for Pattern Analysis and Understanding
- pages
- 1 - 22
- publisher
- CRC Press
- external identifiers
-
- scopus:85052673784
- ISBN
- 9781498769358
- 9781498769372
- DOI
- 10.1201/9781315154152
- language
- English
- LU publication?
- no
- id
- 6eea2b86-e8a8-4d44-bf17-9965e8a68638
- date added to LUP
- 2019-04-02 09:43:56
- date last changed
- 2024-03-02 23:46:35
@inbook{6eea2b86-e8a8-4d44-bf17-9965e8a68638,
abstract = {{<p>This chapter proposes a novel offline text dependent writer verification method based on Gray Level Co-occurrence Matrix (GLCM). The method is used to combine the result of Dual Tree Complex Wavelet Transforms (DT-CWT) and GLCM features to enhance the GLCM feature performance. The texture is a very important characteristic, which is used to verify the known writer from unknown writers. We have used 615 documents from 123 writers producing 43665 numbers of Bangla Isolated characters. The results show that these selected texture features have high distinction accuracy and hence is appropriate for efficient use in the challenging task of automatic writer verification.</p>}},
author = {{Paul, Jaya and Sarkar, Anasua and Halder, Chayan and Roy, Kaushik}},
booktitle = {{Hybrid Intelligent Techniques for Pattern Analysis and Understanding}},
isbn = {{9781498769358}},
language = {{eng}},
month = {{01}},
pages = {{1--22}},
publisher = {{CRC Press}},
title = {{Offline writer verification based on Bangla handwritten characters using enhanced textual feature}},
url = {{http://dx.doi.org/10.1201/9781315154152}},
doi = {{10.1201/9781315154152}},
year = {{2017}},
}