Fingerprint ROI Segmentation Based on Deep Learning

被引：0
|
作者：
Stojanovic, Branka [1 ]
Marques, Oge [2 ]
Neskovic, Aleksandar [3 ]
Puzovic, Snezana [1 ]
机构：
[1] Inst Vlatacom, Milutina Milankovica 5, Belgrade 11070, Serbia
[2] Florida Atlantic Univ, Coll Engn & Comp Sci, 777 Glades Rd, Boca Raton, FL 33431 USA
[3] Univ Belgrade, Sch Elect Engn, Bul Kralja Aleksandra 73, Belgrade 11120, Serbia
来源：
2016 24TH TELECOMMUNICATIONS FORUM (TELFOR) | 2016年
关键词：
Deep Learning; CNN; NN; fingerprint; ROI segmentation;
D O I：
暂无
中图分类号：
TN [电子技术、通信技术];
学科分类号：
0809 ;
摘要：
This paper presents a novel method for fingerprint ROI (region of interest) segmentation using Deep learning technique - Convolutional Neural Networks. Experimental results, obtained using a publicly available test database of 200 fingerprint images in two variations - with and without Gaussian noise, demonstrate that this method is competitive with Fourier coefficients and NN based method for fingerprint images without noise, while it significantly outperforms it, in all three figures of merit, for fingerprint images with noise.
引用
收藏
页码：368 / 371
页数：4
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