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Handwritten Signature Verification using Hybrid Wavelet Transform (HWT) – 2
Manoj Chavan, Ravish R. Singh, Vinayak Bharadi

Published in: Journal for Advance Research in Applied Sciences
Volume- 4, Issue-7, pp.174-181, Dec 2017
DPI :-> 16.10089.JARAS.2017.V4I7.174181.2236



Abstract
Offline signatures contains two dimensional image of the signatures. Online signature contains additional dynamic features such as pressure applied by user, speed of writing, method of holding the pen etc. along with two dimensional image of the signatures. The HWT which are formed by using Kronecker product of two transform, has the ability to analyse the signal at global as well as local level. HWT - 2 was applied on the first 128 samples of the pressure parameter and first 1- 16 samples of the output were used as feature vector for signature verification. Using Hidden Markov Model (HMM) based classifier with ergodic model, the performance of the proposed system was analysed. KEKRE 128 offers best performance with FRR & FAR of 13%. Orthogonal DCT transform, DCT HADAMARD, DHT DCT and HAAR HADAMARD transform offers best performance of 4 training samples. KEKRE 128 offers best performance for 2 to 4 states and DCT KEKRE 128 offers best performance for state 5. The best performance is at 500 symbols by KEKRE 128 and DCT KEKRE.

Key-Words / Index Term
HMM, HWT - 2, Online Signature Verification, FRR, FAR, EER.

How to cite this article
Manoj Chavan, Ravish R. Singh, Vinayak Bharadi , “Handwritten Signature Verification using Hybrid Wavelet Transform (HWT) – 2”, Journal for Advance Research in Applied Sciences, 4, Issue-7, pp.174-181, Dec 2017. DPI:16.10089.JARAS.V4.I7.2236