NDLI: Performance comparison of local directional pattern to local binary pattern in off-line signature verification system

Content Provider	IEEE Xplore Digital Library
Author	Bo Xu Daozhi Lin Longbiao Wang Hongyang Chao Weifeng Li Qinmin Liao
Copyright Year	2014
Description	Author affiliation: Dept. of Electron. Eng., Tsinghua Univ., Shenzhen, China (Bo Xu; Weifeng Li; Qinmin Liao) \|\| Sch. of Software, Sun Yat-sen Univ., Guangzhou, China (Daozhi Lin; Hongyang Chao) \|\| Nagaoka Univ. of Technol., Nagaoka, Japan (Longbiao Wang)
Abstract	There are several papers about pseudo dynamic methods used in signature authentication. Recently, the gray scale features local binary pattern(LBP) originate from texture analysis has been widely used in signature verification system with advantage of robustness to illumination change. The major problem of LBP is its sensitivity to noise, hence many solutions has been applied to solve this problem. In this paper, we further study the performance of LBP in terms of different blocks, then Local directional pattern is explored to obtain a stable and effective feature with the same blocks as LBP. The experiments done with GPDS960Graysignature database demonstrate the effectiveness of LBP and LDP, LBP performs a little better than LDP while LBP has higher dimensions than LDP while the classifier is deployed by Linear Support Vector Machines (SVMs).
Starting Page	308
Ending Page	312
File Size	125833
Page Count	5
File Format	PDF
ISBN	9781479958351
DOI	10.1109/CISP.2014.7003797
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-10-14
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Training Image edge detection Feature extraction Forgery Robustness Kernel
Content Type	Text
Resource Type	Article

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