1. CSN
  2. All Volumes and Issues
  3. Number 881, 2017
  4. Multi-processor computer vision system

Multi-processor computer vision system

CSN.
2017;
, Number 881
: pp. 125 - 128
https://doi.org/10.23939/csn2017.881.125

Puyda V. Multi-processor computer vision system / V. Puyda // Visnyk Natsionalnoho universytetu "Lvivska politekhnika". Serie: Kompiuterni systemy ta merezhi. — Lviv : Vydavnytstvo Lvivskoi politekhniky, 2017. — No 881. — P. 125–128.

Authors:
  1. Volodymyr Puida
1
Lviv Polytechnic National University, Computer Engineering Department

We propose a computer vision system based on multi-processor architecture that uses multi-port memory with equal access to all special microprocessors.

computer vision system
video stream
image segmentation
identification
  1. Baya H., Essa A., Tuytelaarsb T., Van Goola L. Speeded-Up Robust Features (SURF), Computer Vision and Image Understanding 110 (2008), No. 3, 346–359.
  2. Nobuyuki Otsu (1979). A threshold selection method from gray-level histograms. IEEE Trans. Sys., Man., Cyber. 9: R., 62–66.
  3. Anjos A. and Shahbazkia H. Bi-Level Image Thresholding – A Fast Method. BIOSIGNALS 2008. Vol: 2. P: 70–76.
  4. Pujda V. Ja. Realizatsija algorytmu pokadrovogo vyznachennja koordynat obekta u monohromnomu videopototsi., Visnyk "Kompjuterni nauky ta informatsijni tehnologii", Lviv: NU "Lvivska politehnika", 2015, No. 830, P. 136–140.
  5. Pujda V. Ja., Torubka T. V. Vydalennja impulsnyh zavad na zobrazhennja litalnyh aparativ, Visnyk NU "Lvivska politehnika", 2009, No. 658: Kompjuterni systemy ta merezhi, P. 123–127.
  6. Oleksiv M. V., Pujda V. Ja. Metod vizualnogo vyjavlennja ta identyfikatsii litakiv, Visnyk NU "Lvivska politehnika", 2010, No. 688: "Kompjuterni systemy ta merezhi", P. 179–183.
  7. Pujda V. Ja., Torubka T. V. Doslidzhennja algorytmu vyjavlennja ruhomyh litalnyh aparativ na videozobrazhenni stseny, Visnyk NU "Lvivska politehnika", 2011, No. 717:"Kompjuterni systemy ta merezhi", P. 178–181.