版权说明 操作指南
首页 > 成果 > 详情

Multiscale Gaussian Markov Random Fields for Writer Identificatio

认领
导出
Link by DOI
反馈
分享
QQ微信 微博
成果类型:
期刊论文、会议论文
作者:
Ning, Liangshuo*;Zhou, Long;You, Xinge;Du, Liang;He, Zhengyu
通讯作者:
Ning, Liangshuo
作者机构:
[Ning, Liangshuo] Hubei Univ, Fac Math & Comp Sci, Wuhan, Peoples R China.
[Ning, Liangshuo; Zhou, Long; You, Xinge] Wuhan Polytech Univ, Elect & Informat Engn Dept, Wuhan, Peoples R China.
[He, Zhengyu; You, Xinge; Du, Liang] Huazhong Univ Sci & Technol, Elect & Informat Engn Dept, Wuhan, Peoples R China.
[He, Zhengyu] Harbin Inst Technol, Shenzhen Grad Sch, Dept Comp Sci & Technol, Shenzhen, Peoples R China.
通讯机构:
[Ning, Liangshuo] H
Hubei Univ, Fac Math & Comp Sci, Wuhan, Peoples R China.
语种:
英文
期刊:
PROCEEDINGS OF THE 2010 INTERNATIONAL CONFERENCE ON WAVELET ANALYSIS AND PATTERN RECOGNITION
年:
2010
页码:
170-175
会议名称:
2010 International Conference on Wavelet Analysis and Pattern Recognition
会议论文集名称:
International Conference on Wavelet Analysis and Pattern Recognition
会议时间:
JUL 11-14, 2010
会议地点:
Qingdao, PEOPLES R CHINA
会议主办单位:
[Ning, Liangshuo] Hubei Univ, Fac Math & Comp Sci, Wuhan, Peoples R China.^[Ning, Liangshuo;Zhou, Long;You, Xinge] Wuhan Polytech Univ, Elect & Informat Engn Dept, Wuhan, Peoples R China.^[You, Xinge;Du, Liang;He, Zhengyu] Huazhong Univ Sci & Technol, Elect & Informat Engn Dept, Wuhan, Peoples R China.^[He, Zhengyu] Harbin Inst Technol, Shenzhen Grad Sch, Dept Comp Sci & Technol, Shenzhen, Peoples R China.
会议赞助商:
IEEE
出版地:
345 E 47TH ST, NEW YORK, NY 10017 USA
出版者:
IEEE
ISBN:
978-1-4244-6531-6
基金类别:
NSFCNational Natural Science Foundation of China (NSFC) [60803056, 60773187, 60973154]; Ministry of Education, ChinaMinistry of Education, China [NCET -07-0338]
机构署名:
本校为其他机构
院系归属:
电气与电子工程学院
摘要:
Writer identification recently has been considerably studied due to its various applications in forensic and commercial sections. Because offline, text-independent writer identification has limited requirements in writing sample collection, it has wider applications and meanwhile more difficult to handle. By considering handwriting images as visually distinctive textures, we propose a new method for offline, text-independent writer identification based on multiscale version of Gaussian Markov Random Fields (GMRF) model. The handwriting features are extracted in wavelet domain of handwriting te...

反馈

验证码:
看不清楚,换一个
确定
取消

成果认领

标题:
用户 作者 通讯作者
请选择
请选择
确定
取消

提示

该栏目需要登录且有访问权限才可以访问

如果您有访问权限,请直接 登录访问

如果您没有访问权限,请联系管理员申请开通

管理员联系邮箱:yun@hnwdkj.com