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.

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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