Yazar "Türk, Mustafa" seçeneğine göre listele

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    Öğe
    Implementation of Mainly Used Edge Detection Algorithms on FPGA
    (İsmail SARITAŞ, 2016) İçer, Yaser; Türk, Mustafa
    Edge detection has important applications area in image processing field. Today, it is a fact that the image processing used in many fields. Therefore, the applicability of edge detection process in the field is also has great importance. In this study, mainly used edge detection algorithms in the literature; İe. Sobel, Prewitt and Canny algorithms is provided using the verification and inspection on FPGA (Field Programmable Gate Arrays). Program files required for FPGA is prepared by Xilinx System Generator DSP blocks, which can work integrated with Matlab/Simulink. For this study; gray format images, which is stored on the computer has been sent to FPGA with USB configuration port interface on FPGA. Edge detection process is realized by moving subject images from the computer with the same connection to FPGA and then, Sobel, Prewitt and Canny algorihms are applied to the images on FPGA respectively. Edge detection process for the same images are performed by Simulink and FPGA bord at the same time and then, edge detected images obtained from these two environment are compared and also it has been observed on the FPGA resource usage.
  • [ X ]
    Öğe
    Removal of impulse noise in digital images with na¨ıve Bayes classifier method
    (2016) Budak, Cafer; Toprak, Abdullah; Türk, Mustafa
    A new method has been presented in this paper to remove randomly formed impulse noise in digital images. This method is one of the favorite learning approaches of the Bayes learning method and is frequently called the na¨ıve Bayes classifier. It has especially been used more frequently in recent times in the field of signal processing. Prior to restoration of the noisy pixels of the image as is done here, the image is first separated into pieces, and then an associated learning set is formed for each piece using the noise-free pixels. These learning sets that are different for each piece are used in order to estimate the pixel that will replace the noisy one. The proposed method is both simple and easy to apply. Our comprehensive experimental studies show that our proposed method outperforms other filters that are very popular in the literature.