Paper
18 April 2008 Fingerprint separation: an application of ICA
Author Affiliations +
Abstract
Among all existing biometric techniques, fingerprint-based identification is the oldest method, which has been successfully used in numerous applications. Fingerprint-based identification is the most recognized tool in biometrics because of its reliability and accuracy. Fingerprint identification is done by matching questioned and known friction skin ridge impressions from fingers, palms, and toes to determine if the impressions are from the same finger (or palm, toe, etc.). There are many fingerprint matching algorithms which automate and facilitate the job of fingerprint matching, but for any of these algorithms matching can be difficult if the fingerprints are overlapped or mixed. In this paper, we have proposed a new algorithm for separating overlapped or mixed fingerprints so that the performance of the matching algorithms will improve when they are fed with these inputs. Independent Component Analysis (ICA) has been used as a tool to separate the overlapped or mixed fingerprints.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Meenakshi Singh, Deepak Kumar Singh, and Prem K. Kalra "Fingerprint separation: an application of ICA", Proc. SPIE 6982, Mobile Multimedia/Image Processing, Security, and Applications 2008, 69820L (18 April 2008); https://doi.org/10.1117/12.777541
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CITATIONS
Cited by 13 scholarly publications.
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KEYWORDS
Independent component analysis

Neurons

Algorithm development

Neural networks

Performance modeling

Data modeling

Biometrics

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