A Suggested System For Palmprint Recognition Using Curvelet Transform And Co-Occurrence Matrix.

The main purpose of this paper is to create a palmprint recognition system (PPRS) that uses the curvelet transform and co-occurrence matrix to recognize a hand's palmprint. <br /> The suggested system is composed of several stages: in the first stage, the region of interest (ROI) was take...

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Autor principal:	meaad alhadidi
Formato:	article
Lenguaje:	AR EN
Publicado:	College of Education for Pure Sciences 2021
Materias:	region of interest,, ,،,؛unsharp masking,, ,،,؛features extraction,, ,،,؛aco Education L Science (General) Q1-390
Acceso en línea:	https://doaj.org/article/ce04d5f17fbf41288e441a44fe545474
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id	oai:doaj.org-article:ce04d5f17fbf41288e441a44fe545474
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spelling	oai:doaj.org-article:ce04d5f17fbf41288e441a44fe5454742021-12-01T14:54:26ZA Suggested System For Palmprint Recognition Using Curvelet Transform And Co-Occurrence Matrix.1812-125X2664-253010.33899/edusj.2021.130870.1176https://doaj.org/article/ce04d5f17fbf41288e441a44fe5454742021-12-01T00:00:00Zhttps://edusj.mosuljournals.com/article_168846_f1c92b26f0aada0a9f594903961ee44c.pdfhttps://doaj.org/toc/1812-125Xhttps://doaj.org/toc/2664-2530The main purpose of this paper is to create a palmprint recognition system (PPRS) that uses the curvelet transform and co-occurrence matrix to recognize a hand's palmprint. <br /> The suggested system is composed of several stages: in the first stage, the region of interest (ROI) was taken from a palmprint image, then in the second stage, the curvelet transform was applied to the (ROI) to get a blurred version of the image, and finally, unsharp masking process and sobel filtering were done for edge detection. The third stage involves feature extraction using a co-occurrence matrix to obtain 16 features, while the fourth stage inclusion is the training and testing of the suggested approach. The algorithm ACO (ant colony optimization) has been adopted to evaluate the shortest path to the goal.<br /> CASIA PalmprintV dataset of 100 people (60 male and 40 female) was used in proposed work to rate the performance of the proposed system. ARR and EER metrics have been adopted to assess the performance of the proposed system. <br /> The experimental results showed a very high recognition rate (ARR) that reaches 100% for the right hand of a male and the left hand of a female. The overall accuracy rate (ARR) reaches 98.5% and EER equals 0.015.meaad alhadidiCollege of Education for Pure Sciencesarticleregion of interest,,,،,؛unsharp masking,,,،,؛features extraction,,,،,؛acoEducationLScience (General)Q1-390ARENمجلة التربية والعلم, Vol 30, Iss 5, Pp 65-76 (2021)
institution	DOAJ
collection	DOAJ
language	AR EN
topic	region of interest,, ,،,؛unsharp masking,, ,،,؛features extraction,, ,،,؛aco Education L Science (General) Q1-390
spellingShingle	region of interest,, ,،,؛unsharp masking,, ,،,؛features extraction,, ,،,؛aco Education L Science (General) Q1-390 meaad alhadidi A Suggested System For Palmprint Recognition Using Curvelet Transform And Co-Occurrence Matrix.
description	The main purpose of this paper is to create a palmprint recognition system (PPRS) that uses the curvelet transform and co-occurrence matrix to recognize a hand's palmprint. <br /> The suggested system is composed of several stages: in the first stage, the region of interest (ROI) was taken from a palmprint image, then in the second stage, the curvelet transform was applied to the (ROI) to get a blurred version of the image, and finally, unsharp masking process and sobel filtering were done for edge detection. The third stage involves feature extraction using a co-occurrence matrix to obtain 16 features, while the fourth stage inclusion is the training and testing of the suggested approach. The algorithm ACO (ant colony optimization) has been adopted to evaluate the shortest path to the goal.<br /> CASIA PalmprintV dataset of 100 people (60 male and 40 female) was used in proposed work to rate the performance of the proposed system. ARR and EER metrics have been adopted to assess the performance of the proposed system. <br /> The experimental results showed a very high recognition rate (ARR) that reaches 100% for the right hand of a male and the left hand of a female. The overall accuracy rate (ARR) reaches 98.5% and EER equals 0.015.
format	article
author	meaad alhadidi
author_facet	meaad alhadidi
author_sort	meaad alhadidi
title	A Suggested System For Palmprint Recognition Using Curvelet Transform And Co-Occurrence Matrix.
title_short	A Suggested System For Palmprint Recognition Using Curvelet Transform And Co-Occurrence Matrix.
title_full	A Suggested System For Palmprint Recognition Using Curvelet Transform And Co-Occurrence Matrix.
title_fullStr	A Suggested System For Palmprint Recognition Using Curvelet Transform And Co-Occurrence Matrix.
title_full_unstemmed	A Suggested System For Palmprint Recognition Using Curvelet Transform And Co-Occurrence Matrix.
title_sort	suggested system for palmprint recognition using curvelet transform and co-occurrence matrix.
publisher	College of Education for Pure Sciences
publishDate	2021
url	https://doaj.org/article/ce04d5f17fbf41288e441a44fe545474
work_keys_str_mv	AT meaadalhadidi asuggestedsystemforpalmprintrecognitionusingcurvelettransformandcooccurrencematrix AT meaadalhadidi suggestedsystemforpalmprintrecognitionusingcurvelettransformandcooccurrencematrix
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A Suggested System For Palmprint Recognition Using Curvelet Transform And Co-Occurrence Matrix.

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