An Effective Method of Fingerprint Classification Combined with AFIS

Hsieh, Ching-Tang; Shyu, Shys-Rong; Hu, Chia-Shing

doi:10.1007/11596356_110

Cited by 5 publications

(2 citation statements)

References 10 publications

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“…The persistence and degradation rate of fingerprints depends on many factors, such as sex, BMI (body mass index), and environmental conditions, as confirmed in previous research by Czech et al [18,19]. The subject of the persistence and degradation rate of fingerprints consisting of sweat and sebum can also be found in numerous publications, which indicates that it has already been well researched [20,21] There is little information, however, about the persistence of bloody fingerprints. Blood left at the scene of a crime constitutes extremely useful evidence in criminal investigations.…”

Section: Introductionmentioning

confidence: 85%

The impact of time, environmental conditions, and sex on the degradation of bloody fingerprints on a glass surface

Czech

Szabelak

Sowiński

et al. 2021

Journal of Forensic Sciences

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Dactyloscopy is the branch of forensics that deals with identifying individuals by analyzing the configurations of the friction ridges on the fingertips. The persistence and degradation of fingerprints depends on such factors as the individual's sex and BMI (body mass index) and the duration and conditions of their preservation. There is a great deal of information on how the passage of time affects the image of fingerprints composed of sebum and sweat, but little knowledge concerning the preservation of bloody fingerprints. The aim of the study was to determine the effect of sex, the state of the blood forming the print (dry vs. fresh), environmental factors (room vs. outdoor conditions), and time on the width of friction ridge impressions in fingerprints. Fingerprints made with fresh blood were found to persist longest, while prints left by women and exposed to outdoor conditions degraded most rapidly. The ambient temperature also had a significant effect on the width of friction ridge impressions and their degradation.

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Section: Introductionmentioning

confidence: 85%

The impact of time, environmental conditions, and sex on the degradation of bloody fingerprints on a glass surface

Czech

Szabelak

Sowiński

et al. 2021

Journal of Forensic Sciences

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“…Fingerprints are the unique characteristic of humanity. Fingerprint classification restores computational complexity by reducing the number of candidate campaigns to be preceded [8]. Fingerprint images are widely used in different systems, such as personal empathy, access control, Internet authentication and the generation of encryption keys due to their durability, uniqueness and distinctive character.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Fingerprint Identification using Neural Network and BAT Algorithm

Borra¹,

Reddy²,

Reddy³

2018

IJECE

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The uniqueness, firmness, public recognition, and its minimum risk of intrusion made fingerprint is an expansively used personal authentication metrics. Fingerprint technology is a biometric technique used to distinguish persons based on their physical traits. Fingerprint based authentication schemes are becoming increasingly common and usage of these in fingerprint security schemes, made an objective to the attackers. The repute of the fingerprint image controls the sturdiness of a fingerprint authentication system. We intend for an effective method for fingerprint classification with the help of soft computing methods. The proposed classification scheme is classified into three phases. The first phase is preprocessing in which the fingerprint images are enhanced by employing median filters. After noise removal histogram equalization is achieved for augmenting the images. The second stage is the feature Extraction phase in which numerous image features such as Area, SURF, holo entropy, and SIFT features are extracted. The final phase is classification using hybrid Neural for classification of fingerprint as fake or original. The neural network is unified with BAT algorithm for optimizing the weight factor.

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