2015 IEEE 7th International Conference on Biometrics Theory, Applications and Systems (BTAS) 2015
DOI: 10.1109/btas.2015.7358782
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On smartphone camera based fingerphoto authentication

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Cited by 70 publications
(31 citation statements)
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“…Mac et al [9] proposed a methodology for contactless FP recognition including segmentation and feature extraction as well as feature and data fusion and reported an EER of approximately 5%. Sankaran et al [10] used a deep learning (DL)-based approach, a scattering network algorithm (ScatNet), for feature representation and comparison. They evaluated different existing FP recognition algorithms, focusing on photometric effects and performing experiments using various illumination conditions as well as two backgrounds (indoor and outdoor).…”
Section: Related Workmentioning
confidence: 99%
See 1 more Smart Citation
“…Mac et al [9] proposed a methodology for contactless FP recognition including segmentation and feature extraction as well as feature and data fusion and reported an EER of approximately 5%. Sankaran et al [10] used a deep learning (DL)-based approach, a scattering network algorithm (ScatNet), for feature representation and comparison. They evaluated different existing FP recognition algorithms, focusing on photometric effects and performing experiments using various illumination conditions as well as two backgrounds (indoor and outdoor).…”
Section: Related Workmentioning
confidence: 99%
“…Sankaran et al. [ 10 ] used a deep learning (DL)-based approach, a scattering network algorithm (ScatNet), for feature representation and comparison. They evaluated different existing FP recognition algorithms, focusing on photometric effects and performing experiments using various illumination conditions as well as two backgrounds (indoor and outdoor).…”
Section: Introductionmentioning
confidence: 99%
“…The simplest approach to acquire a touchless fingerprint is to capture a 2D fingerphoto using a less costly camera. In the literature, various attempts [9][10][11][12] are made to acquire a fingerphoto using a smartphone camera and various segmentation approaches to obtain a touchless fingerprint from a fingerphoto. In [9], the authors have proposed an approach based on Scattering Wavelet Network to extract texture-based features [13] for matching fingerphotos captured from mobile phone cameras.…”
Section: Related Workmentioning
confidence: 99%
“…The sample images from the database are shown in figure 3. Currently, smartphone-captured touchless fingerphoto databases are available [9,11], which are captured in an unconstrained environment and requires segmentation for further processing. The utilization of bounding box [20] for implementing our touchless fingerprint database eliminates the need for segmentation and minimizes the effect of scaling, rotation and translation on the fingerprint images.…”
Section: Touchless and Touch-based Fingerprint Databasementioning
confidence: 99%
“…Sankaran et al . [19] described a fingerphoto verification by using the mobile phone camera. In this paper, the FT is used with the fingerprint.…”
Section: Prior Workmentioning
confidence: 99%