Fingerprint minutiae filtering based on multiscale directional information

Popović, B.D.; Mašković, Ljiljana

doi:10.2298/fuee0702233p

Cited by 5 publications

(2 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Person recognition by comparison of fingerprint samples with other, already known prints (picture with picture), is not recommended because it often does not give an accurate result. The reasons for the appearance of errors are interference during fingerprinting, scratches, and other damage to the skin in the part from which the fingerprint is taken, then different positions of the finger, as well as deformation of the fingerprint during fingerprinting [18] (Figure 1). The way to recognize and compare fingerprints is to extract details, so-called characteristic points (minutiae) from the image of the fingerprint, using AFIS.…”

Section: Fingerprint For Identification Purposesmentioning

confidence: 99%

Determining the Identity of Corpses Using Fingerprints: Results from Practice and Analysis of Process Used in the Republic of Serbia

Petrovic,

Stojicic,

Radovanovic

et al. 2024

Perspectives in Legal and Forensic Sciences

View full text Add to dashboard Cite

In today's world, when there is a constant fight against organized crime and terrorism, when we have cases of mass accidents (plane crashes, train crashes, buses, etc.), the constant need for precise and quick identification of persons is evident in these cases. When we have situations with a large number of dead in various conditions, as well as complete or only parts of the body being on the spot, there is a need to use scientific and forensic methods in order to find out the reliable identity of these people. Furthermore, there is a need, in some cases, to identify persons who committed suicide, were killed, or died a natural death (accidental death) and who do not have documents according to which their identity can be determined. The aim of this paper will, however, be to identify a group of persons who need to be identified, known as unidentified corpses. Method. Describe and discuss the way of determining identity based on dactyloscopic data, which provides accurate and unambiguous identification, using fingerprints. Results. The identity was determined in 1271 cases of unidentified corpses by dactyloscopic comparison of fingerprints with a database containing fingerprints of about 8,000,000 indisputably identified persons. It was confirmed in 1139 cases. Conclusion. The high degree of identification in our research, as much as 89.6%, makes this method rightly represented as a standard method for confirming a person's identity.

show abstract

Section: Fingerprint For Identification Purposesmentioning

confidence: 99%

Determining the Identity of Corpses Using Fingerprints: Results from Practice and Analysis of Process Used in the Republic of Serbia

Petrovic,

Stojicic,

Radovanovic

et al. 2024

Perspectives in Legal and Forensic Sciences

View full text Add to dashboard Cite

show abstract

“…For the minutiae extraction method we used the one presented in [5], which contains the following steps: segmentation (based on variance calculation in a block); enhancement (proposed method, STFT method and Gabor-based method); binarisation (with log operator and threshold); thinning (skeletonisation) and minutiae detection and verification (by calculating crossing number (CN) in 3 × 3 neighbourhood [1], with some postprocessing involved). A fingerprint expert was previously asked to extract true minutiae from the original fingerprint.…”

mentioning

confidence: 99%

Robust enhancement of fingerprint images obtained by ink method

Popović¹,

Bandjur

Raicevic

2010

Electron. Lett.

View full text Add to dashboard Cite

A method for fingerprint enhancement in the frequency domain based on directional log-Gabor filtering is proposed. Experimental results show that the method can successfully enhance even low-quality fingerprint images obtained by the ink method, outperforming standard, well-known techniques including Gabor filtering.Introduction: To utilise automatic fingerprint identification systems (AFIS) in law enforcement agencies, the first step is to digitalise an archive of fingerprints obtained by the ink method. The quality of those fingerprint images greatly depends on the fingerprint acquisition device (equipment and technique) that is used, but there are also a number of factors (postnatal marks, occupational marks, creases, etc.) that contribute to a large number of spurious minutiae detected, decreasing the overall AFIS performance. That is the reason why enhancement is usually performed before minutiae extraction [1]. When dealing with a particular fingerprint image, i.e. latent, we can apply any of many digital techniques and filters, even combining and adjusting them for that particular case. However, in the case of making a database of fingerprint templates for AFIS from an archive of cards of fingerprints usually taken by ink, the process of automatic minutiae extraction is rarely intervened with by a human expert, so an enhancement method needs to be robust and applicable to a wide range of input images. In the literature, several filters have been proposed in the spatial [2] and frequency [3,4] domains. In this Letter, a robust enhancement algorithm in the frequency domain is proposed. It is based first on amplifying the dominant frequencies by a factor of raised power spectrum (noise reduction) and then by appropriate filtering with a log-Gabor filter (directional enhancement). The results prove to be preferable compared to the standard Gaborbased filtering method.

show abstract

Transform Domain Fingerprint Identification Based on DTCWT

George¹,

K²,

Raja³

2012

IJACSA

View full text Add to dashboard Cite

Abstract-The physiological biometric characteristics are better compared to behavioral biometric identification of human beings to identify a person. In this paper, we propose Transform Domain Fingerprint Identification Based on DTCWT. The original Fingerprint is cropped and resized to suitable dimension to apply DTCWT. The DTCWT is applied on Fingerprint to generate coefficient which form features. The performance analysis is discussed with different levels of DTCWT and also with different sizes of Fingerprint database. It is observed that the recognition rate is better in the case of level 7 compared to other levels of DTCWT.

show abstract

Fingerprint minutiae filtering based on multiscale directional information

Cited by 5 publications

References 15 publications

Determining the Identity of Corpses Using Fingerprints: Results from Practice and Analysis of Process Used in the Republic of Serbia

Determining the Identity of Corpses Using Fingerprints: Results from Practice and Analysis of Process Used in the Republic of Serbia

Robust enhancement of fingerprint images obtained by ink method

Transform Domain Fingerprint Identification Based on DTCWT

Contact Info

Product

Resources

About