Browsing by Subject "Thresholding"
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Item Open Access Durağan olmayan çok bileşenli boğucu sinyaller için yeni bir uyarlanır karışma çıkarıcı analizi(IEEE, 2005) Durak, L.; Arıkan, Orhan; Song, I.A novel adaptive short-time Fourier transform (STFT) implementation for the analysis of non-stationary multi-component jammer signals is introduced. The proposed time-frequency distribution is the fusion of optimum STFTs of individual signal components that are based on the recently introduced generalized time-bandwidth product (GTBP) definition. The GTBP optimal STFTs of the components are combined through thresholding and obtaining the individual component support images, which are related with the corresponding GTBP optimal STFTs.Item Open Access Fast processing techniques for accurate ultrasonic range measurements(Institute of Physics Publishing, 2000) Barshan, B.Four methods of range measurement for airborne ultrasonic systems - namely simple thresholding, curve-fitting, sliding-window, and correlation detection - are compared on the basis of bias error, standard deviation, total error, robustness to noise, and the difficulty/complexity of implementation. Whereas correlation detection is theoretically optimal, the other three methods can offer acceptable performance at much lower cost. Performances of all methods have been investigated as a function of target range, azimuth, and signal-to-noise ratio. Curve fitting, sliding window, and thresholding follow correlation detection in the order of decreasing complexity. Apart from correlation detection, minimum bias and total error is most consistently obtained with the curve-fitting method. On the other hand, the sliding-window method is always better than the thresholding and curve-fitting methods in terms of minimizing the standard deviation. The experimental results are in close agreement with the corresponding simulation results. Overall, the three simple and fast processing methods provide a variety of attractive compromises between measurement accuracy and system complexity. Although this paper concentrates on ultrasonic range measurement in air, the techniques described may also find application in underwater acoustics.Item Open Access Gauss tabanlı modelleme kullanarak canlı hücre görüntülerinin öğreticisiz bölütlenmesi(2011-04) Arslan, Salim; Durmaz, İrem; Çetin-Atalay, Rengül; Gündüz-Demir, ÇiğdemThe first step of targeted cancer drug development is to screen and determine drug candidates by in vitro measuring the effectiveness of the drugs. The tests developed for this purpose can be time consuming due to their procedures and cannot be conducted in every laboratory due to the required hardwares. On the other hand, an image-based screening test has a potential to be less time consuming since it can directly be carried out on the live cell images and to be more extensively used because of the availability of its required equipments and their relatively less expensive cost. With such an image-based test, it is possible to quantify the cell death by finding cellular regions and comparing it against the control group. In this work, we propose a new method that automatically locates the cellular regions by the unsupervised segmentation of live cell images. This method relies on approximately locating cellular regions and the background with gradient-based thresholding and morphological operators and then finding the final boundaries by modeling the gradient of these regions with Gaussians. Working on the images of different cell lines captured with different magnifications, our experiments show that the proposed method leads to promising results. © 2011 IEEE.Item Open Access Image histogram thresholding using Gaussian kernel density estimation (English)(IEEE, 2013) Suhre, Alexander; Çetin, A. EnisIn this article, image histogram thresholding is carried out using the likelihood of a mixture of Gaussians. In the proposed approach, a prob ability density function (PDF) of the histogram is computed using Gaussian kernel density estimation in an iterative manner. The threshold is found by iteratively computing a mixture of Gaussians for the two clusters. This process is aborted when the current bin is assigned to a different cluster than its predecessor. The method does not envolve an exhaustive search. Visual examples of our segmentation versus Otsu's thresholding method are presented. © 2013 IEEE.