Yazarlar

• Akçay, Latif(1)
• Sürer, Bartu(1)
• Velu, Sabareesh K.P.(1)
• Yalçin, Berna Ors(1)
• Yücel, Harun(1)

• BildiriAçık Erişim2022/r/bayburt/14117
  Implementation of a SoC by Using lowRISC Architecture on an FPGA for Image Filtering Applications

  Akçay, Latif; Sürer, Bartu; Yalçin, Berna Ors

  In this study, it is aimed to implement the lowRISC system-on-chip, which is based on the Rocket processor created with the RISC-V instruction set architecture developed by Berkeley University, on FPGA and to run image processing algorithms on this system. While making this implementation, the main target is a system that is very simple, consumes low power, and can be quickly redirected to other purposes. Therefore, it is based on the effective evaluation of the existing system without using any extra customized accelerators. Thus, a free, open source, and powerful enough platform for many embedded system applications is proposed to the designers. For this purpose, a lane detection application designed with standard C libraries such as Gaussian blur filter, Sobel operation filter and other elements, which are widely used in image processing applications, is run with embedded Linux operating system and the results are shared.

  AtıfOpenAlex1

  İncele
• MakaleAçık Erişim2021Scopus SJRQ1/r/bayburt/12098
  Toolbox for tracking and analyzing crowded mixture of colloidal particles

  Yücel, Harun; Velu, Sabareesh K.P.

  We present a MATLAB-based multiple particle tracking (mPosTracker) algorithm to detect and track crowded colloidal particles that are two-dimensionally imaged using digital video microscopy. Our algorithm adopts three optional detection methods using threshold settings namely; centroid method (CM), radial symmetry method (RSM) and partial radial symmetry method (pRSM). In contrast to other reported algorithms, it allows classifying a maximum of three types of particles based on area or intensity. Furthermore, we include a toolbox to perform quantitative particle analysis like number density, trajectories with mean square displacement, and Voronoi cells with six-fold bond parameters to reveal the physics of examined dataset. To demonstrate the abilities of mPosTracker, we show the analysis outcomes on synthetically and experimentally acquired time-lapse microscopy datasets. mPosTracker is suitable for studying the dynamics of crowd behaviour, self-assembly, and manipulation of multi-component colloids under external fields.

  AtıfScopus2·WoS2·OpenAlex2

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