Yazar "Findik, Oguz" seçeneğine göre listele

Listeleniyor 1 - 7 / 7
  • Küçük Resim Yok
    Öğe
    A color image watermarking scheme based on artificial immune recognition system
    (PERGAMON-ELSEVIER SCIENCE LTD, 2011) Findik, Oguz; Babaoglu, Ismail; Ulker, Erkan
    This study suggests a novel watermarking technique that uses artificial immune recognition system to protect color image's intellectual property rights. The watermark is embedded in the blue channel of a color image. m-bit binary sequence embedded into the color image is used to train artificial immune recognition system. With this composed technique, extracting the watermark which is embedded into the color image is carried out using artificial immune recognition system. It is observed that the composed technique achieves high performance to process of extracting this watermark. The watermark is extracted successfully from the watermarked image after various image processing attacks as well. (C) 2010 Elsevier Ltd. All rights reserved.
  • Küçük Resim Yok
    Öğe
    Color Image Watermarking Scheme Based on Efficient Preprocessing and Support Vector Machines
    (SPRINGER-VERLAG BERLIN, 2008) Findik, Oguz; Bayrak, Mehmet; Babaoglu, Ismail; Comak, Emre
    This paper suggests a new block based watermarking technique utilizing preprocessing and support vector machine (PPSVMW) to protect color image's intellectual property rights. Binary test set is employed here to train support vector machine (SVM). Before adding binary data into the original image, blocks have been separated into two parts to train SVM for better accuracy. Watermark's I valued bits were randomly added into the first block part and 0 into the second block part. Watermark is embedded by modifying the blue channel pixel value in the middle of each block so that watermarked image could be composed. SVM was trained with set-bits and three other features which are averages of the differences of pixels in three distinct shapes extracted from each block, and hence without the need of original image, it could be extracted. The results of PPSVMW technique proposed in this study were compared with those of the Tsai's technique. Our technique was proved to be more efficient.
  • Küçük Resim Yok
    Öğe
    A directed artificial bee colony algorithm
    (ELSEVIER, 2015) Kiran, Mustafa Servet; Findik, Oguz
    Artificial bee colony (ABC) algorithm has been introduced for solving numerical optimization problems, inspired collective behavior of honey bee colonies. ABC algorithm has three phases named as employed bee, onlooker bee and scout bee. In the model of ABC, only one design parameter of the optimization problem is updated by the artificial bees at the ABC phases by using interaction in the bees. This updating has caused the slow convergence to global or near global optimum for the algorithm. In order to accelerate convergence of the method, using a control parameter (modification rate-MR) has been proposed for ABC but this approach is based on updating more design parameters than one. In this study, we added directional information to ABC algorithms, instead of updating more design parameters than one. The performance of proposed approach was examined on well-known nine numerical benchmark functions and obtained results are compared with basic ABC and ABCs with MR. The experimental results show that the proposed approach is very effective method for solving numeric benchmark functions and successful in terms of solution quality, robustness and convergence to global optimum. (C) 2014 Elsevier B.V. All rights reserved.
  • Küçük Resim Yok
    Öğe
    EFFECT OF DISCRETIZATION METHOD ON THE DIAGNOSIS OF PARKINSON'S DISEASE
    (ICIC INTERNATIONAL, 2011) Kaya, Ersin; Findik, Oguz; Babaoglu, Ismail; Arslan, Ahmet
    Implementing different classification methods, this study analyzes the effect of discretization on the diagnosis of Parkinson's disease. Entropy-based discrelization method is used as the discretization method, and support vector machines, C4.5, k-nearest neighbors and Naive Bayes are used as the classification methods. The diagnosis of Parkinson's disease is implemented without using any preprocessing method. Afterwards, the Parkinson's disease dataset is classified after implementing entropy-based discretization on the dataset. Both results are compared, and it is observed that using discretization method increases the success of classification on the diagnosis of Parkinson's disease by 4.1% to 12.8%.
  • Küçük Resim Yok
    Öğe
    IMPLEMENTATION OF BCH CODING ON ARTIFICIAL NEURAL NETWORK-BASED COLOR IMAGE WATERMARKING
    (ICIC INTERNATIONAL, 2011) Findik, Oguz; Babaoglu, Ismail; Ulker, Erkan
    This study suggests a novel watermarking technique that uses artificial neural networks (ANN) and BCH (Bose, Chaudhuri and Hocquenghem) coding together to protect intellectual property rights of a color image. BCH error correction coding method is used to improve the performance of watermark extracting. With this composed technique, image is divided into sub-blocks, and a bit-sequence which is used to train both ANN and the watermark is added to the selected sub-blocks. In the watermark embedding process, besides embedding the bit-sequence as is, the watermark is embedded by encoding the watermark into the original image through BCH coding method. ANN is trained by using the features obtained from the selected sub-blocks to which the bit-sequence is embedded. The extraction process is implemented by using the trained ANN and the features obtained from the selected sub-blocks to which the encoded watermark is embedded. After the extraction process, the extracted watermark is obtained by using BCH decoding method. The results of the study are obtained by using the watermark as is and by encoding with BCH coding method. By using BCH encoding method, watermark extraction success is considerably increased, especially on the watermark extraction cases with low success rates. The watermark is extracted considerably successfully from the watermarked image after various image processing attacks as well.
  • Küçük Resim Yok
    Öğe
    A NOVEL HYBRID CLASSIFICATION METHOD WITH PARTICLE SWARM OPTIMIZATION AND K-NEAREST NEIGHBOR ALGORITHM FOR DIAGNOSIS OF CORONARY ARTERY DISEASE USING EXERCISE STRESS TEST DATA
    (ICIC INTERNATIONAL, 2012) Babaoglu, Ismail; Findik, Oguz; Ulker, Erkan; Aygul, Nazif
    The aim of this study is to investigate the effectiveness of a novel hybrid method, particle swarm optimization with k-nearest neighbor classifier (PSOkNN), on determination of coronary artery disease (CAD) existence upon exercise stress testing (EST) data. The PSOkNN method is composed of two steps. At the first step, one particle which demonstrates the whole samples optimally in training dataset is generated for both healthy and unhealthy patients. Then, at the second one, the class of the test sample is determined according to the distance of the test sample to the generated particles utilizing k-nearest neighbor algorithm. To demonstrate the effectiveness of this novel method, the results of PSOkNN are compared with the classification results of the artificial immune recognition system and k-nearest neighbor algorithm. Besides, reliability of the proposed method on determination of CAD existence upon EST data is examined by using classification accuracy, k-fold cross-validation method and Cohen's kappa coefficient.
  • Küçük Resim Yok
    Öğe
    Using Chaotic System in Encryption
    (SPRINGER-VERLAG BERLIN, 2010) Findik, Oguz; Kahramanli, Sirzat
    In this paper chaotic systems and RSA encryption algorithm are combined in order to develop an encryption algorithm which accomplishes the modern standards. E.Lorenz's weather forecast' equations which are used to simulate non-linear systems are utilized to create chaotic map. This equation can be used to generate random numbers. In order to achieve up-to-date standards and use online and offline status, a new encryption technique that combines chaotic systems and RSA encryption algorithm has been developed. The combination of RSA algorithm and chaotic systems makes encryption system.