DocumentCode :
598016
Title :
Latent fingerprint detection and segmentation with a directional total variation model
Author :
Jiangyang Zhang ; Rongjie Lai ; Kuo, C.-J.J.
Author_Institution :
Ming Hsieh Dept. of Electr. Eng., Univ. of Southern California, Los Angeles, CA, USA
fYear :
2012
fDate :
Sept. 30 2012-Oct. 3 2012
Firstpage :
1145
Lastpage :
1148
Abstract :
Latent fingerprint detection and segmentation play a critical role in image forensics for law enforcement. Being collected from crime scenes, a latent fingerprint is often mixed with other components such as structured noise or other fingerprints. Existing fingerprint recognition algorithms fail to work properly for latent fingerprint images, since they are mostly applicable under the assumption that the image is already properly segmented and there is no overlap between the target fingerprint and other components. In this work, we present a novel directional total variation (DTV) model to achieve effective latent fingerprint detection and segmentation. As compared with existing total variation models, the proposed DTV model differentiates itself by considering spatial-dependent texture orientations in the TV computation, which is particularly suitable for images with oriented textures. We demonstrate the superior performance of the proposed DTV technique using images from the NIST SD27 latent fingerprint database.
Keywords :
fingerprint identification; image segmentation; image texture; DTV model; DTV technique; NIST SD27 latent fingerprint database; directional total variation; directional total variation model; latent fingerprint detection; latent fingerprint images; latent fingerprint segmentation; spatial-dependent texture orientations; structured noise; Adaptation models; Computational modeling; Digital TV; Estimation; Image segmentation; Noise; Noise measurement; Latent fingerprint; directional total variation; fingerprint segmentation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing (ICIP), 2012 19th IEEE International Conference on
Conference_Location :
Orlando, FL
ISSN :
1522-4880
Print_ISBN :
978-1-4673-2534-9
Electronic_ISBN :
1522-4880
Type :
conf
DOI :
10.1109/ICIP.2012.6467067
Filename :
6467067
Link To Document :
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