Image Quality Assessment for Fake Biometric Detection: Application to Iris, Fingerprint and Face Recognition
Abstract: Image Quality Assessment (IQA) is one of the statistical techniques used in image processing to determine whether the biometric sample is real or fake. The objective of the system is to enrich the biometric recognition security. This paper deals with two distinct measures of IQA. The first measure is Full-Reference (FR) IQA consists of a 2D image extracting different image quality features using a reference image which is filtered by a technique called Gaussian filtering. The second measure is No-Reference (NR) IQA used to estimate the quality level of an image. Eventually, 26 image quality features are exacted to minimize the degree of complexity. Quality of test sample implies to results of the following process of classification based on IQA. Presented paper briefly introduces the IQA theory and its measures.
Keywords: Image Quality Assessment IQA, biometrics, liveness detection
How to Cite?: Parul Gupta, Neetu Gyanchandani, "Image Quality Assessment for Fake Biometric Detection: Application to Iris, Fingerprint and Face Recognition", Volume 6 Issue 5, May 2017, International Journal of Science and Research (IJSR), Pages: 2166-2169, https://www.ijsr.net/getabstract.php?paperid=ART20173847, DOI: https://dx.doi.org/10.21275/ART20173847