Browsing by Author "Elbasi, E."

Now showing 1 - 4 of 4

Citation - Scopus: 4
Dynamic Binary Location Based Multi-Watermark Embedding Algorithm in Dwt
(Asian Research Publishing Network, 2015) Hussein, A.J.; Yuksel, S.; Elbasi, E.
In order to achieve a good imperceptibility and robustness, using 4-level DWT algorithm based on dynamic binary host image location and embedding two watermark logos in different DWT levels are proposed for copyright protection and authenticity. In the propounded watermarking algorithm, 5-level DWT is applied to host image to obtain the fifth low frequency sub band (LL5), and examination the dynamic binary location value of selected location for embedding purpose in five different locations in host image using the same algorithm process. Our experimental results demonstrate that our algorithm scheme is imperceptible and robust against several image processing attacks, and watermarked image quality evaluating by calculation of SNR, PSNR, RMSE, and MAE. © 2005 - 2015 JATIT & LLS. All rights reserved.
Citation - Scopus: 4
Hough Transform Based Watermark Embedding Algorithm in Dct Frequency Domain
(Asian Research Publishing Network, 2017) Alsultan, M.; Alramli, T.; Albayati, A.; Elbasi, E.
In this paper, an algorithm has been proposed that makes use of Hough transform to locate the positions of lines in the cover image. The watermark was embedded in these positions in the original DCT domain. The robustness of the new algorithm has been evaluated and the experimental results were compared with the Chaotic Sequence Based Watermarking algorithm, which also work in the DCT domain. The Compression has been done depending on the Performance evaluation for imperceptibility and robustness of proposed algorithms. Several attacks were also used and peak signal to noise ratio (PSNR) value was calculated for cover image and watermarked image. Similarity ratio (SR) for the extracted watermark was also calculated. The Hough-based Watermark technique has been found robust against Gaussian, Histogram, Intensity, Gamma and Corp attacks. Whereas, the Chaotic-based Watermark technique was observed robust against Gaussian, Mean filter, Rotation, Histogram, Intensity, Gamma and Corp attacks. © 2005 – ongoing JATIT & LLS.
Citation - WoS: 10
Citation - Scopus: 12
A New Robust Binary Image Embedding Algorithm in Discrete Wavelet Domain
(Institute of Electrical and Electronics Engineers Inc., 2014) Mohammed, A.; Maraş, H.H.; Elbasi, E.; 34410
Digital watermarks have recently emerged as a possible solution for protecting the copyright of digital materials, the work presented in this paper is concerned with the Discrete Wavelet Transform (DWT) based non-blind digital watermarking, and how the DWT is an efficient transform in the field of digital watermarking. In this work we used an optimum criteria that embeds four watermarks in more than one level of DWT in the same algorithm. The aim of this work is to keep the Correlation Coefficient (CC) between the original and the extracted watermark around the value of 0.9.
Petrol Flow Pattern Identification Via Data Mining Techniques
(2012) Olcer, N.; Elbasi, E.
Nowadays, petrol is an important resource for whole world, researchers are working on several mathematical models for flow pattern identification. One previous study is to find characterization of reservoir modeling in petrol flow data. Spatial data-mining can be used in reservoir geological research and ranking reservoir modeling. To find petrol flow patterns there is a study which aims to investigate and analyze the hole cleaning performance of gasified drilling fluids in horizontal, directional and vertical wells experimentally. Also, to identify the drilling parameters those have the major influence on cuttings transport, to define the flow pattern types and boundaries as well as to observe the behavior of cuttings in detail by using digital image processing techniques, and to develop a mechanistic model based on the fundamental principles of physics and mathematics with the help of the experimental observations. In this study we worked on petrol flow data with following features: mud flow rate, mud superficial velocity, pipe rotation per minute, rate of penetration, pressure transmitter and drill pipe. These features have been used in different classification and clustering algorithms to classify in nine class; Dispersed, Moving Bed, Stationary Bed, Dispersed Annular, Bubble, Elongated Bubble, Slug, Wavy Stratified, and Wavy Annular.We have received very promising results from 93% to 100% accuracy using different data mining algorithms. © Sila Science.