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Hardware Centric Machine Vision For High Precision Center Of Gravity Calculation

Authors: Cheng, Xin; Thörnberg, Benny; Malik, Abdul Waheed; Najeem Lawal;

Hardware Centric Machine Vision For High Precision Center Of Gravity Calculation

Abstract

{"references": ["Larsson U., Zell C., Hyypp\u251c\u00f1 K., Wernersson \u00c5.: Navigating an\nArticulated Vehicle and Reversing with a Trailer. Proceedings 1994\nIEEE International Conference on Robotics and Automation, vol. 3, pp.\n2398--2404, San Diego, USA (1994).", "Wolf W., Ozer C., Lv T.: Smart cameras as embedded systems.\nComputer, vol. 35, no. 9 (2002).", "Dias F., Berry F., Serot J., Marmoiton F.: Hardware, design and\nimplementation issues on a fpga-based smart camera. Proc. First\nACM/IEEE international conference on distributed smart cameras. pp\n20--26, Vienna, Austria (2007).", "Carsten Steger, Markus Ulrich and Christian Wiedemann,Machine\nvision algorithms and applications, Wiley-VCH 2008.", "Wnuk M.: Remarks on hardware implementation of image processing\nalgorithms. Int. journal of applied mathematics and computer science.\nVol. 18, No. 1, pp105--110 (2008).", "H. C. van Assen, M. Egmont-Petersen, and J. H. C. Reiber, \"Accurate\nObject Localization in Gray Level Images Using the Center of Gravity\nMeasure: Accuracy Versus Precision, IEEE Transaction on Image\nProcessing,\" Vol. 11, No.12 December 2002.", "R.C. Gonzales and R.E. Woods, Addison Wesley,Digital Image\nProcessing, 2008, third edition.", "A. Patwardhan, Subpixel position measurement using 1D,2D and 3D\ncentroid algorithms with emphasis on applications in confocal\nmicroscopy, Journal of Microscopy, Vol. 186,Pt 3, June 1997, pp. 246-\n257.", "Alexander Fish, Dmitry Akselrod and Orly Yadid-Pecht-Pecht, High\nPrecision Image Centroid Computation via an Adaptive K-Winner-\nTake-all Circuit in Conjunction with a Dynamic Element Matching\nAlgorithm for Star Tracking Applications, Analog Integrated Circuits\nand Signal Processing, 39, 251-266, 2004.\n[10] G.A.W. West, & T.A. Clarke, 1990, \"A survey and examination of\nsubpixel measurement techniques.\", ISPRS Int. Conf. on Close Range\nPhotogrammetry and Machine Vision, SPIE Vol. 1395, pp 456 - 463,\nSept. 3-7.\n[11] Clarke, T.A. Cooper, M.A.R. & Fryer, J.G., 1993. An estimator for the\nrandom error in subpixel target location and its use in the bundle\nadjustment. Optical 3-D measurements techniques II, Pub. Wichmann,\nKarlsruhe:161-168.\n[12] B.Th\u00f6rnberg et al. \"Bit-Width Constrained Memory Hierarchy\nOptimization for Real-Time Video Systems\", IEEE Transactions on\nComputer-Aided Design of Integrated Circuits and Systems, Vol26, No\n4, pp 781-800, April 2007.\n[13] B. Th\u00f6rnberg and N. Lawal, \"Real-time component labelling and feature\nextraction on FPGA\", Proc. of International Symposium on Signals,\nCircuits and Systems, Iasi, Romania 2009,"]}

We present a hardware oriented method for real-time measurements of object-s position in video. The targeted application area is light spots used as references for robotic navigation. Different algorithms for dynamic thresholding are explored in combination with component labeling and Center Of Gravity (COG) for highest possible precision versus Signal-to-Noise Ratio (SNR). This method was developed with a low hardware cost in focus having only one convolution operation required for preprocessing of data.

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Keywords

Dynamic thresholding, sub-pixel precision, segmentation, center of gravity., position measurement

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
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