期刊名称：Signal & Image Processing : An International Journal (SIPIJ)
印刷版ISSN：2229-3922
电子版ISSN：0976-710X
出版年度：2014
卷号：5
期号：3
页码：13
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：The paper presents to address this challenge, we have proposed the use of Adaptive Window Positioningtechnique which focuses on not just the meaning of the handwritten signature but also on the individualityof the writer. This innovative technique divides the handwritten signature into 13 small windows of size nxn(13x13). This size should be large enough to contain ample information about the style of the author andsmall enough to ensure a good identification performance. The process was tested with a GPDS datasetcontaining 4870 signature samples from 90 different writers by comparing the robust features of the testsignature with that of the user’s signature using an appropriate classifier. Experimental results reveal thatadaptive window positioning technique proved to be the efficient and reliable method for accuratesignature feature extraction for the identification of offline handwritten signatures .The contribution of thistechnique can be used to detect signatures signed under emotional duress.
