@inproceedings{3db7e055346446a7a5deb196bc684613,
title = "Fast fingerprint orientation field estimation incorporating general purpose GPU",
abstract = "Fingerprint is one of the broadly utilized biometric traits for personal identification in both civilian and forensic applications due to its high acceptability, strong security, and low cost. Fingerprint ridge orientation is one of the global fingerprint representations that keeps the holistic ridge structure in a small storage area. The importance of fingerprint ridge orientation comes from its usage in fingerprint singular point detection, coarse level classification, and fingerprint alignment. However, processing time is an important factor in any automatic fingerprint identification system, estimating that ridge orientation image may consume long processing time. This research presents an efficient ridge orientation estimation approach by incorporating a Graphics Processing Unit (GPU) capability to the traditional pixel gradient method. The simulation work shows a significant enhancement in ridge orientation estimation time by 6.41x using a general purpose GPU in comparison to the CPU execution.",
keywords = "Fingerprints, GPU, Parallel processing, Ridge orientation",
author = "Awad, {Ali Ismail}",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016.; 6th International Workshop Soft Computing Applications, SOFA 2014 ; Conference date: 24-07-2014 Through 26-07-2014",
year = "2016",
doi = "10.1007/978-3-319-18416-6_70",
language = "English",
isbn = "9783319184159",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Verlag",
pages = "891--902",
editor = "Balas, {Valentina Emilia} and Branko Kova{\v c}evi{\'c} and Jain, {Lakhmi C.}",
booktitle = "Soft Computing Applications - Proceedings of the 6th International Workshop Soft Computing Applications, SOFA 2014",
address = "Germany",
}