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Latent fingerprint enhancement and segmentation technique based on hybrid edge adaptive DTV model

Image enhancement and segmentation is widely used for fingerprint identification and authorization in biometrics devices, criminal scene is most challenges due to low quality of fingerprint , the most significant efforts is to develop algorithm for latent fingerprint enhancement which become chal...

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Main Authors: Yousef A. Baker, El-Ebiary, Abdilahi, Liban, Abdullah, M.A., Othman A. M., Miaikil, Contreras, Jennifer, Hilles, M.M.
Format: Conference or Workshop Item
Language:English
English
Published: 2021
Subjects:
QA Mathematics
T Technology (General)
Online Access:http://eprints.unisza.edu.my/4328/1/FH03-FIK-21-56518.pdf
http://eprints.unisza.edu.my/4328/2/FH03-FIK-21-54904.pdf
http://eprints.unisza.edu.my/4328/
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spelling my-unisza-ir.43282022-01-03T07:39:20Z http://eprints.unisza.edu.my/4328/ Latent fingerprint enhancement and segmentation technique based on hybrid edge adaptive DTV model Yousef A. Baker, El-Ebiary Abdilahi, Liban Abdullah, M.A. Othman A. M., Miaikil Contreras, Jennifer Hilles, M.M. QA Mathematics T Technology (General) Image enhancement and segmentation is widely used for fingerprint identification and authorization in biometrics devices, criminal scene is most challenges due to low quality of fingerprint , the most significant efforts is to develop algorithm for latent fingerprint enhancement which become challenging problem due to the complex and existing problem for instance, developing algorithms of latent fingerprint is able to extract features of image blocks and removing overlapping and isolate the poor and noisy background. however, it's still challenging and interested problem specifically latent fingerprint enhancement and segmentation . The aim study of this paper is to propose latent fingerprint enhancement and segmentation based on hybrid model and Chan-Vese method for segmentation , in order to reduce low image quality and increase the accuracy of fingerprint . The desired characteristics of intended technique are adaptive, effective and accurate, hybrid model of edge adaptive direction achieves accurate latent fingerprint enhancement and segmentation , the target needs to improve feature detection and performance, this research has proposed system architecture of research method in fingerprint enhancement and segmentation where is the method content two stages, the first is normalization and second is reconstruction, using EDTV model is required for adaptive noise, in addition Chan-vase technique contributed for identification of fingerprint image features, the result and testing using RMSE with three categories of fingerprint images good, bad and ugly show better performance for all three categories, as well RMSE shows the average of good latent fingerprint before and after enhancement . Latent Fingerprint Enhancement and Segmentation Technique Based on Hybrid Model Edge Adaptive Directional Total Variation. 2021 Conference or Workshop Item PeerReviewed text en http://eprints.unisza.edu.my/4328/1/FH03-FIK-21-56518.pdf text en http://eprints.unisza.edu.my/4328/2/FH03-FIK-21-54904.pdf Yousef A. Baker, El-Ebiary and Abdilahi, Liban and Abdullah, M.A. and Othman A. M., Miaikil and Contreras, Jennifer and Hilles, M.M. (2021) Latent fingerprint enhancement and segmentation technique based on hybrid edge adaptive DTV model. In: 2nd International Conference on Smart Computing and Electronic Enterprise, 15-16 Jul 2021, Cameron Highland, Malaysia.
institution Universiti Sultan Zainal Abidin
building UNISZA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Sultan Zainal Abidin
content_source UNISZA Institutional Repository
url_provider https://eprints.unisza.edu.my/
language English
English
topic QA Mathematics
T Technology (General)
spellingShingle QA Mathematics
T Technology (General)
Yousef A. Baker, El-Ebiary
Abdilahi, Liban
Abdullah, M.A.
Othman A. M., Miaikil
Contreras, Jennifer
Hilles, M.M.
Latent fingerprint enhancement and segmentation technique based on hybrid edge adaptive DTV model
description Image enhancement and segmentation is widely used for fingerprint identification and authorization in biometrics devices, criminal scene is most challenges due to low quality of fingerprint , the most significant efforts is to develop algorithm for latent fingerprint enhancement which become challenging problem due to the complex and existing problem for instance, developing algorithms of latent fingerprint is able to extract features of image blocks and removing overlapping and isolate the poor and noisy background. however, it's still challenging and interested problem specifically latent fingerprint enhancement and segmentation . The aim study of this paper is to propose latent fingerprint enhancement and segmentation based on hybrid model and Chan-Vese method for segmentation , in order to reduce low image quality and increase the accuracy of fingerprint . The desired characteristics of intended technique are adaptive, effective and accurate, hybrid model of edge adaptive direction achieves accurate latent fingerprint enhancement and segmentation , the target needs to improve feature detection and performance, this research has proposed system architecture of research method in fingerprint enhancement and segmentation where is the method content two stages, the first is normalization and second is reconstruction, using EDTV model is required for adaptive noise, in addition Chan-vase technique contributed for identification of fingerprint image features, the result and testing using RMSE with three categories of fingerprint images good, bad and ugly show better performance for all three categories, as well RMSE shows the average of good latent fingerprint before and after enhancement . Latent Fingerprint Enhancement and Segmentation Technique Based on Hybrid Model Edge Adaptive Directional Total Variation.
format Conference or Workshop Item
author Yousef A. Baker, El-Ebiary
Abdilahi, Liban
Abdullah, M.A.
Othman A. M., Miaikil
Contreras, Jennifer
Hilles, M.M.
author_facet Yousef A. Baker, El-Ebiary
Abdilahi, Liban
Abdullah, M.A.
Othman A. M., Miaikil
Contreras, Jennifer
Hilles, M.M.
author_sort Yousef A. Baker, El-Ebiary
title Latent fingerprint enhancement and segmentation technique based on hybrid edge adaptive DTV model
title_short Latent fingerprint enhancement and segmentation technique based on hybrid edge adaptive DTV model
title_full Latent fingerprint enhancement and segmentation technique based on hybrid edge adaptive DTV model
title_fullStr Latent fingerprint enhancement and segmentation technique based on hybrid edge adaptive DTV model
title_full_unstemmed Latent fingerprint enhancement and segmentation technique based on hybrid edge adaptive DTV model
title_sort latent fingerprint enhancement and segmentation technique based on hybrid edge adaptive dtv model
publishDate 2021
url http://eprints.unisza.edu.my/4328/1/FH03-FIK-21-56518.pdf
http://eprints.unisza.edu.my/4328/2/FH03-FIK-21-54904.pdf
http://eprints.unisza.edu.my/4328/
_version_ 1720984507083915264
score 13.211869

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