Environmental impact to multimedia systems on the example of fingerprint aging behavior at crime scenes

Merkel, Ronny; Breuhan, Andy; Hildebrandt, Mario; Vielhauer, Claus; Bräutigam, Anja

doi:10.1117/12.922701

Cited by 4 publications

(4 citation statements)

References 3 publications

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“…In prior work [4], we have identified five main influences on the aging behavior of fingerprints captured with a CWL sensor, which are the sweat influence, environmental influence, surface influence, scan influence and application influence, with about 45 potential sub-influences, most of which are investigated in [12], [13], [15] and [16]. We expect these influences to be similar for the aging behavior of fingerprints captured with a flat bed scanner.…”

Section: Influences On the Capturing Processing And Evaluationmentioning

confidence: 91%

“…The binary pixel aging feature offers different preprocessing methods, such as dynamic or static normalization, global thresholding, Otsu thresholding or background masking, which are formalized in [16]. We here only consider a specific sequence of preprocessing steps, which has been shown in prior tests to achieve optimal results and give a formalization of the binary pixel feature calculation for images scanned with the flat bed scanner as well as those scanned with the CWL sensor.…”

Section: Formalization Of the Binary Pixel Featurementioning

confidence: 98%

“…However, some of them are sensor specific and therefore different. In this section, we discuss different influences only for the used flat bed scanner and refer to [12], [13], [15] and [16] for a detailed discussion of such influences on the CWL sensor used here for comparison. We also discuss aspects of the probe fixation, give a formalization of the binary pixel feature and introduce the three fingerprint image quality classes and measures of comparison used in the scope of our experiments.…”

Section: General Aspects Of Fingerprint Acquisition Using Flat Bed Scmentioning

confidence: 99%

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On using flat bed scanners for the age determination of latent fingerprints

Merkel

Vielhauer

2012

Proceedings of the on Multimedia and Security

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Determining the age of latent fingerprints found at crime scenes is a very pressing, yet so far unresolved challenge in forensics. Recently, a first aging feature called binary pixel has been introduced, based on the loss of image contrast of fingerprint time series captured non-invasively with a Chromatic White Light (CWL) sensor. Such new feature seems to be promising, showing a logarithmic behavior for fingerprints when aging. However, a CWL sensor is very expensive, bulky and comparatively slow in the acquisition. We here explore the possibility of using a common flat bed scanner as a cheaper, more flexible and faster alternative to the CWL technique. Comparing 250 fingerprint time series scanned in regular time intervals over a period of 24 hours with a CWL sensor as well as a flat bed scanner (18000 scans in total), our conclusions are threefold: firstly, the binary pixel feature can reliably be produced with a flat bed scanner for scan images of sufficient quality according to our subjective quality metric defined in this paper. Secondly, however, only 24% of flat bed scanner images are of high quality, clearly showing the much higher reliability of CWL results. Thirdly, the experiments furthermore indicate that the binary pixel feature is not sensor specific and can be applied to different image sensors.

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Section: Influences On the Capturing Processing And Evaluationmentioning

confidence: 91%

Section: Formalization Of the Binary Pixel Featurementioning

confidence: 98%

Section: General Aspects Of Fingerprint Acquisition Using Flat Bed Scmentioning

confidence: 99%

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On using flat bed scanners for the age determination of latent fingerprints

Merkel

Vielhauer

2012

Proceedings of the on Multimedia and Security

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“…[10][11][12][13] These sensors can also be used to estimate the age of latent fingerprints left on a variety of surfaces. [14][15][16][17][18][19] Some authors used contactless CWL sensors for determining the age of a fingermark. [14][15][16][17][18][19] They observed that different factors such as composition of sweat, humidity, temperature, ultraviolet (UV) radiation, type of substrate, presence of water-containing substance on fingertip, scan resolution, and measured area size affect the results.…”

Section: Optical Methodsmentioning

confidence: 99%

Emerging latent fingerprint technologies: a review

Bumbrah¹,

Sharma²,

Jasuja³

2016

RRFMS

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Information regarding state of the art technology is accessible by searching in a systematic manner, and is the preferred way of keeping up to date. In this review, we present the recent developments in the field of latent fingerprint detection. Recent developments in processing methods including optical, physical, and chemical methods, and sophistical instrumental analytical techniques are presented.

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