Browsing by Author "Elbasi, Ersin"

Now showing 1 - 6 of 6

Citation - WoS: 3
Citation - Scopus: 4
Block size analysis for discrete wavelet watermarking and embedding a vector image as a watermark
(Zarka Private Univ, 2019) Sever, Hayri; Sever, Hayri; Senol, Ahmet; Elbasi, Ersin; 11916; Bilgisayar Mühendisliği
As telecommunication and computer technologies proliferate, most data are stored and transferred in digital format. Content owners, therefore, are searching for new technologies to protect copyrighted products in digital form. Image watermarking emerged as a technique for protecting image copyrights. Early studies on image watermarking used the pixel domain whereas modern watermarking methods convert a pixel based image to another domain and embed a watermark in the transform domain. This study aims to use, Block Discrete Wavelet Transform (BDWT) as the transform domain for embedding and extracting watermarks. This study consists of 2 parts. The first part investigates the effect of dividing an image into non overlapping blocks and transforming each image block to a DWT domain, independently. Then, effect of block size on watermark success and, how it is related to block size, are analyzed. The second part investigates embedding a vector image logo as a watermark. Vector images consist of geometric objects such as lines, circles and splines. Unlike pixel-based images, vector images do not lose quality due to scaling. Vector watermarks deteriorate very easily if the watermarked image is processed, such as compression or filtering. Special care must be taken when the embedded watermark is a vector image, such as adjusting the watermark strength or distributing the watermark data into the image. The relative importance of watermark data must be taken into account. To the best of our knowledge this study is the first to use a vector image as a watermark embedded in a host image.
Citation - WoS: 6
Citation - Scopus: 7
Blocked-DWT Based Vector Image Watermarking
(Ieee, 2015) Senol, Ahmet; Sever, Hayri; Dincer, Kivanc; Sever, Hayri; Elbasi, Ersin; Bilgisayar Mühendisliği
Image watermarking is in use for proving ownership for a fairly long time. For most of the study on this area, a pseudo random number sequence PRSN or a binary image logo is embedded as watermark. Nowadays the owner's face or sound is also embedded as biometric watermark. Image is transferred to discrete wavelet transform domain, watermark is embedded to DWT values, then DWT values are retransformed to spatial domain to obtain watermarked image. Embedding a vector image logo as watermark was not tried in previous works. In this work, non-blind robust watermarking is applied using a vector image as watermark. Various attacks are applied to watermarked images and for each of these attacks vector image watermark is obtained equal or almost equal to the original. Embedding vector image as watermark will bring a new discipline for image watermarking and a new development will arise in this perspective.
Citation - WoS: 0
Comparison of Data Mining Algorithms for Emg Signals
(Turgut Ozal Univ, 2012) Taskan Demirkok, Burcu; Elbasi, Ersin
The aim of this study is to compare data mining algorithms and having a significant result using selected data mining algorithm on data which was collected during the "The Muscular Activity Analysis of Circumoral and Jaw-Closing Muscles Response To The Trainer on Patients With Class II Malocclusion Using Electromyogram" project. This document gives the accuracy rate of selected data mining algorithms on data set with using WEKA data mining tool.
Citation - WoS: 2
Citation - Scopus: 2
Improvement of DWT-SVD with Curve Fitting and Robust Regression: An Application to Astronomy Images
(Kaunas Univ Technology, 2016) Karadeniz, Talha; Karadeniz, Talha; Elbasi, Ersin; 304886; Yazılım Mühendisliği
DWT-SVD is a frequency domain based eigenanalysis watermarking technique. In this work, we improve this method by exploring the relationship between the cover image's DWT singular values and those of the watermark. We show that, via the usage of curve fitting and robust regression, it is possible to achieve accurate results. We also demonstrate that the improved scheme is suitable for the watermarking of astronomy images. In addition to encoding and decoding examples, statistical results on stealth and robustness are deduced from the experiments so that the clear advance can be observed. Quality of the watermark is measured by testing against various attack types.
Citation - WoS: 0
Citation - Scopus: 11
Measurement of Edge Detection Algorithms in Clean and Noisy Environment
(Ieee, 2014) Mahmood, Alaa Mohammed; Maras, Hadi Hakan; Elbasi, Ersin; 34410
The subject of identification edge in images has a wide application in various fields for that it's considered one of the important topics in a digital image processing. There are many algorithms to detect the edge in images, but the performance of these algorithms depends on the type of image, the environment of the image and the threshold value of the edge algorithm. The objective of this paper is to evaluate five algorithms of edge detection which are Roberts, Sobel, Prewitt, LOG, and Canny in multi environments clean and noisy by using several types of original images (binary image, graphic image, high frequency image, low frequency image, median frequency image, and texture image) and then determine the best algorithm. In noisy environment the following noises was used Gaussian, salt and pepper and speckle. It's known that each edge detection algorithm has a threshold value, if the current pixel value is less than the defined threshold in strength, it will be considered an edge pixel. The change rate of the threshold value in all environments is also explained through this study.
Citation - WoS: 5
Citation - Scopus: 23
Robust Medical Image Watermarking Using Frequency Domain and Least Significant Bits Algorithms
(Ieee, 2018) Kaya, Volkan; Elbasi, Ersin
Watermarking and stenography are getting importance recently because of copyright protection and authentication. In watermarking we embed stamp, logo, noise or image to multimedia elements such as image, video, audio, animation, software and text. There are several works have been done in watermarking for different purposes. In this research work we used watermarking techniques to embed patient information into the medical magnetic resonance (MR) images. There are two methods have been used; frequency domain (Digital Wavelet Transform-DWT, Digital Cosine Transform-DCT and Digital Fourier Transform-DFT) and spatial domain (Least Significant Bits-LSB). Experimental results show that embedding in frequency domains resist against one group of attacks, and embedding in spatial domain is resist against another group of attacks. Peak Signal Noise Ratio (PSNR) and Similarity Ratio (SR) values are two measurement values for testing. This two values gives very promising result for information hiding in medical MR images.