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Enhanced Approach on Online Handwritten Signature Verification through Multi rate SVM with Wavelet Transformation
Open Access   Article

Enhanced Approach on Online Handwritten Signature Verification through Multi rate SVM with Wavelet Transformation
Prathibha MK1 , Basavaraj L2

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-7 , Page no. 58-65, Jul-2018


Online published on Jul 31, 2018

Copyright © Prathibha MK, Basavaraj L . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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IEEE Style Citation: Prathibha MK, Basavaraj L, “Enhanced Approach on Online Handwritten Signature Verification through Multi rate SVM with Wavelet Transformation”, International Journal of Computer Sciences and Engineering, Vol.6, Issue.7, pp.58-65, 2018.

MLA Style Citation: Prathibha MK, Basavaraj L "Enhanced Approach on Online Handwritten Signature Verification through Multi rate SVM with Wavelet Transformation." International Journal of Computer Sciences and Engineering 6.7 (2018): 58-65.

APA Style Citation: Prathibha MK, Basavaraj L, (2018). Enhanced Approach on Online Handwritten Signature Verification through Multi rate SVM with Wavelet Transformation. International Journal of Computer Sciences and Engineering, 6(7), 58-65.
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Abstract :
Online Handwritten Signature verification plays a significant role in the field of administrative, banking, business sector, etc. Therefore, an accurate signature verification system is required in order to provide an identification of an individual. A new Online Handwritten Signature verification is proposed based on a Multirate Support Vector Machine (MSVM) and for verification the SUSIG database is used. The input database is obtained from the pressure sensitive tablet, removal of noise and resizing is done through fourth order wavelet and discrete cosine transform. Further, the functional feature such as standard deviation, skewness etc. are extracted and processed to MSVM for generation of threshold value between genuine and sample signature. The obtained result is more sensitive, specific and accurate. The Equal Error rate (EER) of 0.33 is obtained, so that the proposed system shows competitive performance with the other existing approaches.
Key-Words / Index Term :
Online Handwritten Signature Verification,(OHSV), Multirate Support Vector Model (MSVM), Discrete, Wavelet Transform (DWT), Discrete Cosine Transformation (DCT), Feature Extraction, Forgery, Threshold value
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