Quality Assessment and Identification of Fingerprints by Analysis of the Image’s Structural Properties
https://doi.org/10.30764/1819-2785-2020-4-90-97
Abstract
The paper addresses the problem of assessing the quality of fingerprint images using spatial analysis methods. The author proposes using the previously developed mathematical model to describe the set of magnitudes of the image gradient. The model is based on the two-parameter Weibull distribution. The author proposes two approaches to assess the quality of fingerprints. The first approach is implemented by the so-called “Full reference method”, which compares the Weibull distribution parameters’ values of statistical estimates. The results of identifying sweat pores using this method are presented. The second approach is called the “No-Reference method” and is used to assess fingerprints’ quality when analyzing and identifying the information content of their individual sections. It is proposed to use an image blur map as a quality characteristic and a statistical estimate of the Weibull distribution shape parameter as a measure of the blur. The shape parameter is estimated at each image point by the combination of magnitudes of the image gradient in the vicinity of the point; in this, the previously developed blur mapping technique is applied. The specific examples illustrate effectiveness of the proposed approaches.
About the Author
D. G. Asatryan
Institute for Informatics and Automation Problems of National Academy of Sciences of Armenia; Russian-Armenian University
Armenia
Armenia
Asatryan David Geghamovich – Doctor of Engineering, Leading Scientist of the Institute for Informatics and Automation Problems of National Academy of Sciences of Armenia, Head of the Research Center for Critical Technologies of Russian-Armenian University
Yerevan 0014
Yerevan 0052
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Review
For citations:
Asatryan D.G. Quality Assessment and Identification of Fingerprints by Analysis of the Image’s Structural Properties. Theory and Practice of Forensic Science. 2020;15(4):90-97. (In Russ.) https://doi.org/10.30764/1819-2785-2020-4-90-97
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