**4. Conclusions**

In this paper, we propose a two-stage method using SCs and FF for accurate online signature verification. Features of SCs are extracted from the input firstly and classification of this stage is based on shape distance metric. Only the inputs passing by the first stage are represented by a set of FF and verified. To improve the matching accuracy and efficiency, we propose a SC-DTW to compare the test signature with the enrolled reference ones based on the extracted FF. Then an interval-valued symbolic representation-based classifier is proposed to decide if the test signature is a genuine one. The proposed method is evaluated on SVC2004 Task 2 database achieving an EER of 2.39% which is competitive to the state-of-the-art approaches. The experiment results demonstrate the effectiveness of the proposed method.

**Author Contributions:** L.H., Y.J. and H.C. contributed to algorithm and system design; Y.J. conducted the experiments; L.H. and Y.J. contributed to experiment results analysis and manuscripts.

**Funding:** This research was funded by National Natural Science Foundation of China (NSFC) grant number 61271306.

**Acknowledgments:** The authors thank for the help of reviewers and editors.

**Conflicts of Interest:** The authors declare no conflict of interest.
