User Identification Based on the Dynamic Features Extracted from Handwriting on Touchscreen Devices
DOI:
https://doi.org/10.3991/ijim.v14i11.11859Keywords:
User identification, user identification on smartphone, security on smartphone, Dynamic time warping, dynamic features, mobile computing, and handwriting based finger on smartphone.Abstract
Abstract - This research presents a methodology for user identification using ten English words written by a finger on smartphone and mini-tablet. This research considers three features, namely Signature Precision (SP), Finger Pressure (FP), and Movement Time (MT) that were extracted from each of ten English words using dynamic time warping. The features are then used individually and combined for the purpose of user identification based on the Euclidean distance and the k-nearest neighbor classifier. We concluded that the best identification accuracy results from the combinations of (SP and FP) features with an average accuracies of 74.55% and 69% were achieved on small smartphone and Mini-tablet respectively using a dataset of 42 users.
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Published
2020-07-10
How to Cite
Al-Showarah, S., Alzyadat, W., Alhroob, A., & Al-Assam, H. (2020). User Identification Based on the Dynamic Features Extracted from Handwriting on Touchscreen Devices. International Journal of Interactive Mobile Technologies (iJIM), 14(11), pp. 126–136. https://doi.org/10.3991/ijim.v14i11.11859
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