scholarly journals Automated region masking of latent overlapped fingerprints

2017 ◽  
Author(s):  
K Tejas ◽  
C Swathi ◽  
D Aravind Kumar ◽  
Rajesh Muthu
Keyword(s):  
Overlapped Fingerprints

scholarly journals FinSNet: End-to-End Separation of Overlapped Fingerprints Using Deep Learning

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 209020-209029
Author(s):  
Dongheon Yoo ◽  
Jaebum Cho ◽  
Juhyun Lee ◽  
Minseok Chae ◽  
Byounghyo Lee ◽  
...  
Keyword(s):  
Deep Learning ◽  
End To End ◽  
Overlapped Fingerprints

scholarly journals Separating Overlapped Fingerprints

2011 ◽  
Vol 6 (2) ◽  
pp. 346-359 ◽  
Author(s):  
Fanglin Chen ◽  
Jianjiang Feng ◽  
Anil K. Jain ◽  
Jie Zhou ◽  
Jin Zhang
Keyword(s):  
Overlapped Fingerprints

scholarly journals The overlapped latent fingerprint separation by using Fourier Optics (FO)

2021 ◽  
Vol 2145 (1) ◽  
pp. 012055
Author(s):  
Nichchar Sommit ◽  
Ratchapak Chitaree
Keyword(s):  
Image Processing ◽  
Crime Scene ◽  
Processing Technique ◽  
Spatial Domain ◽  
Personal Identification ◽  
Image Processing Technique ◽  
Fourier Optics ◽  
Periodic Pattern ◽  
Latent Fingerprints ◽  
Overlapped Fingerprints

Abstract Latent fingerprints are one of the most important pieces of evidence left at a crime scene and can be linked to all individuals involved. Each person’s fingerprints are unique and permanent, becoming an ideal biometric trait for the personal identification by extracting and comparing characteristic points (minutiae) of ridges. The overlapping fingerprint cases are frequently encountered in a crime scene and causing a difficult interpretation for an investigator. The problem has been challenging for forensic scientists over a decade. The method proposed in this study for the separation of overlapped latent fingerprints is based on the well-known spatial filtering method in the Fourier Optics (FO). Instead of tackling the problem by experiment, an alternative and simple means of image processing was proposed and conducted. The working principles start form converting spatial domain patterns (an image of overlapped fingerprints) to spatial frequency domain patterns or power spectrum, filtering out unwanted components (unwanted fingerprint) by appropriate spatial filters, and finally converting the modified pattern back to spatial domain patterns (an image of suspect fingerprint). As a result, the final image is improved from its original state. The periodic pattern of ridges is the key that allows FO to be used in the separation of the overlapped fingerprints. In this work, the procedures described are simply performed by an open source software: ImageJ. The FO-based image processing technique satisfactorily demonstrated its ability to recover an individual fingerprint from overlapping fingerprints.

Adaptive Orientation Model Fitting for Latent Overlapped Fingerprints Separation

2014 ◽  
Vol 9 (10) ◽  
pp. 1547-1556 ◽  
Author(s):  
Ning Zhang ◽  
Yali Zang ◽  
Xin Yang ◽  
Xiaofei Jia ◽  
Jie Tian
Keyword(s):  
Model Fitting ◽  
Orientation Model ◽  
Overlapped Fingerprints

A novel neural network based approach to latent overlapped fingerprints separation

2016 ◽  
Vol 76 (10) ◽  
pp. 12775-12799 ◽  
Author(s):  
Branka Stojanović ◽  
Aleksandar Nešković ◽  
Oge Marques
Keyword(s):  
Neural Network ◽  
Overlapped Fingerprints

A study of automatic separation and recognition for overlapped fingerprints

2018 ◽  
Vol 71 ◽  
pp. 127-140 ◽  
Author(s):  
Hsieh-Chang Huang ◽  
Ching-Tang Hsieh ◽  
Min-Nan Hsiao ◽  
Cheng-Hsiang Yeh
Keyword(s):  
Overlapped Fingerprints

Effects and Limitations of Separating Overlapped Fingerprints Using Fast Fourier Transform

2019 ◽  
Vol 61 ◽  
pp. 377-400
Author(s):  
Chaewon Kim ◽  
◽  
Chaelin Kim ◽  
Hanna Lee ◽  
Jeseol Yu ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Overlapped Fingerprints
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