Robust image watermarking techniques using image features

This thesis addresses the issue of image watermarking robustness against attacks and especially geometrical attacks. The objectives of this research were, improve robustness watermarking technique based on local image features, and propose robust zero watermarking technique according to the global f...

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Main Author:	Khalid Hassan, Mohamed Edris
Format:	Thesis
Language:	English English
Published:	2016
Subjects:	T Technology (General)
Online Access:	http://umpir.ump.edu.my/id/eprint/15829/ http://umpir.ump.edu.my/id/eprint/15829/ http://umpir.ump.edu.my/id/eprint/15829/1/Robust%20image%20watermarking%20techniques%20using%20image%20features%20-%20Table%20of%20contents%20-FSKKP-Khalid%20Hassan%20Mohamed%20Edris-CD%2010612.pdf http://umpir.ump.edu.my/id/eprint/15829/2/Robust%20image%20watermarking%20techniques%20using%20image%20features%20-%20Abstract%20-FSKKP-Khalid%20Hassan%20Mohamed%20Edris-CD%2010612.pdf

id	ump-15829
recordtype	eprints
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English English
topic	T Technology (General)
spellingShingle	T Technology (General) Khalid Hassan, Mohamed Edris Robust image watermarking techniques using image features
description	This thesis addresses the issue of image watermarking robustness against attacks and especially geometrical attacks. The objectives of this research were, improve robustness watermarking technique based on local image features, and propose robust zero watermarking technique according to the global features of image, To obtain the local feature of image, the feature points extractor is very important. The improved robustness watermarking scheme adopted better feature points extractions named Brief and Efficient Scale Invariant Feature Transform, also adopted another feature points extractions named grouping Harris corner, so they can choose more robust feature points, then increase the robustness of watermark. This scheme used two watermarking techniques, namely, local circular region and block discrete cosine transform, to embed the watermark into two types of regions and extract it. To embed in local circular region, Brief and Efficient Scale Invariant Feature Transform extracts feature points, and then Local Circular Regions for embedding are found, finally, the watermark is embedded into Local Circular Regions by using Histogram. To embed into block discrete cosine transform, grouping Harris corner extracts feature points, and then the image is divided into 80 × 80 non-overlapping block to find candidate blocks, then each candidate block is divided into 8×8 non-overlapping sub-blocks and embeds the watermark in the DC components of each sub-block using its HVS-based embedding strength. For extracting watermark from Local Circular Regions, firstly, robust BE-SIFT feature points is extracted, then, Local Circular Regions are found, finally, the local histogram is computed to extract the watermark. For extracting watermark from Block DCT, first, grouping robust Harris corner feature points is extracted. Second, Delaunay tessellation and triangle matching are applied to restore the probe image. Third, the probe image is divided into 80×80 non-overlapping blocks. Fourth, each block is divided into 8×8 non-overlapping sub-blocks. Fifth, any sub-block is transformed into DCT sub-block. Sixth, the watermark is extracted from DC values. The experimental results showed that the improved scheme is robust against a wide variety of attacks. In particular, it is more robust against geometric attacks. The proposed method has 100% good performance for resisting attacks on Lena and Pepper images, and at least 84% good performance on Barbara and Plane images compared with Deng’s method, and it has 100% good performance compared with other methods. In addition, robust zero watermarking scheme based on global feature of image using complex Zernike moments is proposed, the contribution of this method is adopting complex Zernike moments, which can provide better robustness against geometric attacks and provide more information about image and more space for embedding and zero watermarking. Before calculating complex Zernike moments, standard translation and scaling of the tested image is performed, after getting the binarization of the argument value, the feature image is constructed and XOR operation with logo image is executed to generate verification image. Experimental results demonstrated that the proposed scheme has strong robustness to various attacks especially geometric attacks. The proposed scheme has at least 70% good performance of resisting attacks on tested images compared with the other methods.
format	Thesis
author	Khalid Hassan, Mohamed Edris
author_facet	Khalid Hassan, Mohamed Edris
author_sort	Khalid Hassan, Mohamed Edris
title	Robust image watermarking techniques using image features
title_short	Robust image watermarking techniques using image features
title_full	Robust image watermarking techniques using image features
title_fullStr	Robust image watermarking techniques using image features
title_full_unstemmed	Robust image watermarking techniques using image features
title_sort	robust image watermarking techniques using image features
publishDate	2016
url	http://umpir.ump.edu.my/id/eprint/15829/ http://umpir.ump.edu.my/id/eprint/15829/ http://umpir.ump.edu.my/id/eprint/15829/1/Robust%20image%20watermarking%20techniques%20using%20image%20features%20-%20Table%20of%20contents%20-FSKKP-Khalid%20Hassan%20Mohamed%20Edris-CD%2010612.pdf http://umpir.ump.edu.my/id/eprint/15829/2/Robust%20image%20watermarking%20techniques%20using%20image%20features%20-%20Abstract%20-FSKKP-Khalid%20Hassan%20Mohamed%20Edris-CD%2010612.pdf
first_indexed	2023-09-18T22:20:55Z
last_indexed	2023-09-18T22:20:55Z
_version_	1777415650965192704
spelling	ump-158292017-01-12T05:49:18Z http://umpir.ump.edu.my/id/eprint/15829/ Robust image watermarking techniques using image features Khalid Hassan, Mohamed Edris T Technology (General) This thesis addresses the issue of image watermarking robustness against attacks and especially geometrical attacks. The objectives of this research were, improve robustness watermarking technique based on local image features, and propose robust zero watermarking technique according to the global features of image, To obtain the local feature of image, the feature points extractor is very important. The improved robustness watermarking scheme adopted better feature points extractions named Brief and Efficient Scale Invariant Feature Transform, also adopted another feature points extractions named grouping Harris corner, so they can choose more robust feature points, then increase the robustness of watermark. This scheme used two watermarking techniques, namely, local circular region and block discrete cosine transform, to embed the watermark into two types of regions and extract it. To embed in local circular region, Brief and Efficient Scale Invariant Feature Transform extracts feature points, and then Local Circular Regions for embedding are found, finally, the watermark is embedded into Local Circular Regions by using Histogram. To embed into block discrete cosine transform, grouping Harris corner extracts feature points, and then the image is divided into 80 × 80 non-overlapping block to find candidate blocks, then each candidate block is divided into 8×8 non-overlapping sub-blocks and embeds the watermark in the DC components of each sub-block using its HVS-based embedding strength. For extracting watermark from Local Circular Regions, firstly, robust BE-SIFT feature points is extracted, then, Local Circular Regions are found, finally, the local histogram is computed to extract the watermark. For extracting watermark from Block DCT, first, grouping robust Harris corner feature points is extracted. Second, Delaunay tessellation and triangle matching are applied to restore the probe image. Third, the probe image is divided into 80×80 non-overlapping blocks. Fourth, each block is divided into 8×8 non-overlapping sub-blocks. Fifth, any sub-block is transformed into DCT sub-block. Sixth, the watermark is extracted from DC values. The experimental results showed that the improved scheme is robust against a wide variety of attacks. In particular, it is more robust against geometric attacks. The proposed method has 100% good performance for resisting attacks on Lena and Pepper images, and at least 84% good performance on Barbara and Plane images compared with Deng’s method, and it has 100% good performance compared with other methods. In addition, robust zero watermarking scheme based on global feature of image using complex Zernike moments is proposed, the contribution of this method is adopting complex Zernike moments, which can provide better robustness against geometric attacks and provide more information about image and more space for embedding and zero watermarking. Before calculating complex Zernike moments, standard translation and scaling of the tested image is performed, after getting the binarization of the argument value, the feature image is constructed and XOR operation with logo image is executed to generate verification image. Experimental results demonstrated that the proposed scheme has strong robustness to various attacks especially geometric attacks. The proposed scheme has at least 70% good performance of resisting attacks on tested images compared with the other methods. 2016-09 Thesis NonPeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/15829/1/Robust%20image%20watermarking%20techniques%20using%20image%20features%20-%20Table%20of%20contents%20-FSKKP-Khalid%20Hassan%20Mohamed%20Edris-CD%2010612.pdf application/pdf en http://umpir.ump.edu.my/id/eprint/15829/2/Robust%20image%20watermarking%20techniques%20using%20image%20features%20-%20Abstract%20-FSKKP-Khalid%20Hassan%20Mohamed%20Edris-CD%2010612.pdf Khalid Hassan, Mohamed Edris (2016) Robust image watermarking techniques using image features. PhD thesis, Universiti Malaysia Pahang. http://iportal.ump.edu.my/lib/item?id=chamo:98234&theme=UMP2

Robust image watermarking techniques using image features

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