Forged Signature Distinction Using Convolutional Neural Network for Feature Extraction
AbstractThis paper proposes a dynamic verification scheme for finger-drawn signatures in smartphones. As a dynamic feature, the movement of a smartphone is recorded with accelerometer sensors in the smartphone, in addition to the moving coordinates of the signature. To extract high-level longitudinal and topological features, the proposed scheme uses a convolution neural network (CNN) for feature extraction, and not as a conventional classifier. We assume that a CNN trained with forged signatures can extract effective features (called S-vector), which are common in forging activities such as hesitation and delay before drawing the complicated part. The proposed scheme also exploits an autoencoder (AE) as a classifier, and the S-vector is used as the input vector to the AE. An AE has high accuracy for the one-class distinction problem such as signature verification, and is also greatly dependent on the accuracy of input data. S-vector is valuable as the input of AE, and, consequently, could lead to improved verification accuracy especially for distinguishing forged signatures. Compared to the previous work, i.e., the MLP-based finger-drawn signature verification scheme, the proposed scheme decreases the equal error rate by 13.7%, specifically, from 18.1% to 4.4%, for discriminating forged signatures. View Full-Text
Scifeed alert for new publicationsNever miss any articles matching your research from any publisher
- Get alerts for new papers matching your research
- Find out the new papers from selected authors
- Updated daily for 49'000+ journals and 6000+ publishers
- Define your Scifeed now
Nam, S.; Park, H.; Seo, C.; Choi, D. Forged Signature Distinction Using Convolutional Neural Network for Feature Extraction. Appl. Sci. 2018, 8, 153.
Nam S, Park H, Seo C, Choi D. Forged Signature Distinction Using Convolutional Neural Network for Feature Extraction. Applied Sciences. 2018; 8(2):153.Chicago/Turabian Style
Nam, Seungsoo; Park, Hosung; Seo, Changho; Choi, Daeseon. 2018. "Forged Signature Distinction Using Convolutional Neural Network for Feature Extraction." Appl. Sci. 8, no. 2: 153.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.