The ideal effect of Gabor filters and Uniform Local Binary Pattern combinations on deformed scanned paper images

Existing scanners produce paper images with different types of deformations such as noise, rotation and shear. These deformations affect the accuracy of the fingerprinting the document images, which entails utilizing advanced feature extraction operators. Existing feature extractor such as the Unifo...

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Autores principales:	Shihab Hamad Khaleefah, Salama A. Mostafa, Aida Mustapha, Mohammad Faidzul Nasrudin
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Paper fingerprinting Document authentication Gabor filters (GF) Uniform Local Binary Pattern (ULBP) Electronic computers. Computer science QA75.5-76.95
Acceso en línea:	https://doaj.org/article/e97fa2d3b60b4a11bce6a7728a435655
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spelling	oai:doaj.org-article:e97fa2d3b60b4a11bce6a7728a4356552021-11-22T04:19:41ZThe ideal effect of Gabor filters and Uniform Local Binary Pattern combinations on deformed scanned paper images1319-157810.1016/j.jksuci.2019.07.012https://doaj.org/article/e97fa2d3b60b4a11bce6a7728a4356552021-12-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1319157819301892https://doaj.org/toc/1319-1578Existing scanners produce paper images with different types of deformations such as noise, rotation and shear. These deformations affect the accuracy of the fingerprinting the document images, which entails utilizing advanced feature extraction operators. Existing feature extractor such as the Uniform Local Binary Patterns (ULBP) has been found to be limited in dealing with the global view of the texture and neglecting useful information about the images. This article presents an Automated Paper Fingerprinting (APF) method that deploys a combination approach for Gabor Filters (GF) and Uniform Local Binary Patterns (ULBP) called the GFULBP operator to cater for both local and global image information during the feature extraction process for higher texture classification accuracy. The APF method is evaluated by a standard dataset of 306 blank paper images derived from pre-existing scanner image dataset from Universiti Kebangsaan Malaysia (UKM) with properties ranges from 50 DPI, 100 DPI, and 150 DPI respectively. The images are captured by a flatbed scanner with 50 DPI, 100 DPI, and 150 DPI resolutions. Each image is represented by four patches that are segmented from specific locations of the image. The test results of the APF show that GFULBP is able to outperform the ULBP alone by 30.68% when the GF has a 5 scale and π/2 orientation degree. This work finds that the integration of Gabor filters and ULBP significantly enhances the feature extraction quality and fingerprinting accuracy.Shihab Hamad KhaleefahSalama A. MostafaAida MustaphaMohammad Faidzul NasrudinElsevierarticlePaper fingerprintingDocument authenticationGabor filters (GF)Uniform Local Binary Pattern (ULBP)Electronic computers. Computer scienceQA75.5-76.95ENJournal of King Saud University: Computer and Information Sciences, Vol 33, Iss 10, Pp 1219-1230 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Paper fingerprinting Document authentication Gabor filters (GF) Uniform Local Binary Pattern (ULBP) Electronic computers. Computer science QA75.5-76.95
spellingShingle	Paper fingerprinting Document authentication Gabor filters (GF) Uniform Local Binary Pattern (ULBP) Electronic computers. Computer science QA75.5-76.95 Shihab Hamad Khaleefah Salama A. Mostafa Aida Mustapha Mohammad Faidzul Nasrudin The ideal effect of Gabor filters and Uniform Local Binary Pattern combinations on deformed scanned paper images
description	Existing scanners produce paper images with different types of deformations such as noise, rotation and shear. These deformations affect the accuracy of the fingerprinting the document images, which entails utilizing advanced feature extraction operators. Existing feature extractor such as the Uniform Local Binary Patterns (ULBP) has been found to be limited in dealing with the global view of the texture and neglecting useful information about the images. This article presents an Automated Paper Fingerprinting (APF) method that deploys a combination approach for Gabor Filters (GF) and Uniform Local Binary Patterns (ULBP) called the GFULBP operator to cater for both local and global image information during the feature extraction process for higher texture classification accuracy. The APF method is evaluated by a standard dataset of 306 blank paper images derived from pre-existing scanner image dataset from Universiti Kebangsaan Malaysia (UKM) with properties ranges from 50 DPI, 100 DPI, and 150 DPI respectively. The images are captured by a flatbed scanner with 50 DPI, 100 DPI, and 150 DPI resolutions. Each image is represented by four patches that are segmented from specific locations of the image. The test results of the APF show that GFULBP is able to outperform the ULBP alone by 30.68% when the GF has a 5 scale and π/2 orientation degree. This work finds that the integration of Gabor filters and ULBP significantly enhances the feature extraction quality and fingerprinting accuracy.
format	article
author	Shihab Hamad Khaleefah Salama A. Mostafa Aida Mustapha Mohammad Faidzul Nasrudin
author_facet	Shihab Hamad Khaleefah Salama A. Mostafa Aida Mustapha Mohammad Faidzul Nasrudin
author_sort	Shihab Hamad Khaleefah
title	The ideal effect of Gabor filters and Uniform Local Binary Pattern combinations on deformed scanned paper images
title_short	The ideal effect of Gabor filters and Uniform Local Binary Pattern combinations on deformed scanned paper images
title_full	The ideal effect of Gabor filters and Uniform Local Binary Pattern combinations on deformed scanned paper images
title_fullStr	The ideal effect of Gabor filters and Uniform Local Binary Pattern combinations on deformed scanned paper images
title_full_unstemmed	The ideal effect of Gabor filters and Uniform Local Binary Pattern combinations on deformed scanned paper images
title_sort	ideal effect of gabor filters and uniform local binary pattern combinations on deformed scanned paper images
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/e97fa2d3b60b4a11bce6a7728a435655
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The ideal effect of Gabor filters and Uniform Local Binary Pattern combinations on deformed scanned paper images

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