A high speed robot vision system with GigE vision extension

High speed image and video processing is becoming increasingly important in many applications, especially in robotics. To boost the computing speed of traditional robot vision system, a FPGA and DSP based robot vision system is developed. Considering about the high throughput image acquisition is the premise of high speed processing, a GigE vision interface is also extended. The configuration and some important characteristics of this robot vision system, which can not only capture images rapidly but can also process images using different algorithms in real-time, are described in this paper. Experiment results are also given to show that the newly developed vision system is much faster and more suitable for robot vision applications.

[1]  Peng Lu,et al.  A High Performance Low Power Consumption Robot Vision System , 2007, Third International Conference on Natural Computation (ICNC 2007).

[2]  Xing Zhang,et al.  A Developmental Robot Vision System , 2006, 2006 IEEE International Conference on Systems, Man and Cybernetics.

[3]  Kui Yuan,et al.  An improved Canny edge detector and its realization on FPGA , 2008, 2008 7th World Congress on Intelligent Control and Automation.

[4]  H. GholamHosseini,et al.  A High Speed Vision System for Robots Using FPGA Technology , 2008, 2008 15th International Conference on Mechatronics and Machine Vision in Practice.

[5]  Jae Wook Jeon,et al.  FPGA Design and Implementation of a Real-Time Stereo Vision System , 2010, IEEE Transactions on Circuits and Systems for Video Technology.

[6]  Thambipillai Srikanthan,et al.  An efficient edge and corner detector , 2010, 2010 11th International Conference on Control Automation Robotics & Vision.

[7]  Venkatesan Muthukumar,et al.  Image processing algorithms on reconfigurable architecture using HandelC , 2004 .

[8]  Brian C. Lovell,et al.  A high resolution smart camera with GigE Vision extension for surveillance applications , 2008, 2008 Second ACM/IEEE International Conference on Distributed Smart Cameras.

[9]  Tom Chen,et al.  A Real-Time Edge Detector: Algorithm and VLSI Architecture , 1997, Real Time Imaging.

[10]  Daggu Venkateshwar Rao,et al.  An efficient reconfigurable architecture and implementation of edge detection algorithm using Handle-C , 2004, International Conference on Information Technology: Coding and Computing, 2004. Proceedings. ITCC 2004..