A Two-Stage Method for Online Signature Verification Using Shape Contexts and Function Features
| Autor: | Houjin Chen, Yu Jia, Linlin Huang |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Dynamic time warping
Matching (statistics) Computer science Data_MISCELLANEOUS Word error rate 02 engineering and technology lcsh:Chemical technology Biochemistry Identity (music) Article Analytical Chemistry shape contexts Set (abstract data type) 0202 electrical engineering electronic engineering information engineering lcsh:TP1-1185 Electrical and Electronic Engineering Representation (mathematics) Instrumentation function features two-stage method business.industry 020208 electrical & electronic engineering Pattern recognition Function (mathematics) SC-DTW online signature verification Atomic and Molecular Physics and Optics Signature (logic) symbolic representation 020201 artificial intelligence & image processing Artificial intelligence business |
| Zdroj: | Sensors, Vol 19, Iss 8, p 1808 (2019) Sensors (Basel, Switzerland) Sensors Volume 19 Issue 8 |
| ISSN: | 1424-8220 |
| Popis: | As a behavioral biometric trait, an online signature is extensively used to verify a person&rsquo s identity in many applications. In this paper, we present a method using shape contexts and function features as well as a two-stage strategy for accurate online signature verification. Specifically, in the first stage, features of shape contexts are extracted from the input and classification is made based on distance metric. Only the inputs passing by the first stage are represented by a set of function features and verified. To improve the matching accuracy and efficiency, we propose shape context-dynamic time warping (SC-DTW) to compare the test signature with the enrolled reference ones based on the extracted function features. Then, classification based on interval-valued symbolic representation is employed to decide if the test signature is a genuine one. The proposed method is evaluated on SVC2004 Task 2 achieving an Equal Error Rate of 2.39% which is competitive to the state-of-the-art approaches. The experiment results demonstrate the effectiveness of the proposed method. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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