Interpolation implementation of Bayer pattern to PLIC in video stream processing tasks

Dynamic Urban Surveillance Video Stream Processing Using Fog Computing

2016 IEEE Second International Conference on Multimedia Big Data (BigMM) ◽

10.1109/bigmm.2016.53 ◽

2016 ◽

Cited By ~ 57

Author(s):

Ning Chen ◽

Yu Chen ◽

Yang You ◽

Haibin Ling ◽

Pengpeng Liang ◽

...

Keyword(s):

Fog Computing ◽

Stream Processing ◽

Video Stream ◽

Surveillance Video

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Multifunctional video stream processing system based on DSP

10.1117/12.481567 ◽

2002 ◽

Author(s):

Shengxiang Wang ◽

Hansheng Lu ◽

Zhiyun Gao ◽

Shanfeng Hou

Keyword(s):

Stream Processing ◽

Processing System ◽

Video Stream

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Efficient pre-processing algorithms for an FPGA based in-camera video-stream processing system for industry inspection

CCECE '97. Canadian Conference on Electrical and Computer Engineering. Engineering Innovation: Voyage of Discovery. Conference Proceedings ◽

10.1109/ccece.1997.608373 ◽

2002 ◽

Cited By ~ 2

Author(s):

S.H. Hajimowlana ◽

G.A. Jullien ◽

R. Muscedere ◽

J.W. Roberts

Keyword(s):

Stream Processing ◽

Processing System ◽

Video Stream ◽

Processing Algorithms

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Real-Time Detection of Road Signs

Journal of Electronic Commerce in Organizations ◽

10.4018/jeco.2015070103 ◽

2015 ◽

Vol 13 (3) ◽

pp. 36-46 ◽

Cited By ~ 1

Author(s):

Abderrahim Salhi ◽

Brahim Minaoui ◽

Mohamed Fakir ◽

Mohammed Sajieddine

Keyword(s):

Real Time ◽

Performance Improvement ◽

Programming Language ◽

Detection Method ◽

Stream Processing ◽

Video Stream ◽

Identification System ◽

Polygonal Approximation ◽

Road Signs ◽

Processing Module

In order to realize an identification system of traffic road signs in real time, the authors have developed a performed detection method of these signs in real time. This method, presented in this paper, is implemented in two modules. The first is a pre-processing module based on video stream processing technics and the second, based on the polygonal approximation digital curves, identifies areas that may contain road signs using the particularity of their colors and contours. All algorithms implemented in this work are developed under the programming language C / C ++ using OpenCV library. The results of tests, realized on real videos of the traffic signs, show the performance improvement of the method developed in this work in terms of rate and speed of detection.

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