Yazar "Savas, M. Fatih" seçeneğine göre listele

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    Moving object detection using an adaptive background subtraction method based on block-based structure in dynamic scene
    (Elsevier Gmbh, 2018) Savas, M. Fatih; Demirel, Huseyin; Erkal, Bilgehan
    Today, determining background which forms the basis of the video surveillance system whose use is increasing in parallel with developing technology, is a complicated process to implement for cases involving dynamic scene. In this study, we proposed a block-based adaptive method which can be adaptable to dynamic environmental conditions. By grouping the pixels in the picture frame as 2 x 2 non-overlapped blocks, we reduced the amount of noise and the time delay caused by processing of pixels. By a simple counter structure, we created an adaptive threshold parameter which can be adapted according to the case in N surrounding. We used this parameter to perform an update of the background model and reduced background model normalization process. So, we reduced the update time of background operably. Our proposed method achieved successful results in levels of grey levels. (C) 2018 Elsevier GmbH. All rights reserved.
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    Noise Reduction using MRF and Block-Based Background Modeling in Dynamic Scenes Input
    (Int Journal Computer Science & Network Security-Ijcsns, 2017) Savas, M. Fatih; Demirel, Huseyin
    Identifying the moving foreground object in dynamic scenes and making the analysis of video sequences accurate and powerful is an important process for video surveillance systems. Environmental factors such as environmental noises and sudden light changes are the main factors of the degradation of the background model. Complex algorithms are needed to create a strong background against these factors. In this study, We increased the noise immunity of the background model exposed to environmental noise by applying Markov random field (MRF) to block-based modified KDE (Kernel Density Estimation). We also reduced the storage space requirement with the KDE structure we created in blocks. Thus we have increased the applicability of this structure to a real-time structure.