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Hardware implementation of the Hough Techniques for Irregular Colour and Grey-level Pattern Recognition

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EN
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EN
This paper presents a hardware implementation of the Hough technique applied to the tasks of irregular colour and grey-level pattern recognition. The presented method is based on the Hough Transform with a parameter space defined by translation, rotation and scaling operations. An essential element of this method is the generalisation of the Hough Transform for grey level and colour images. The technique simplifies the application of the Hough Transform to irregular patterns recognition tasks. The hardware implementation accelerates the calculations considerably and may be used in computer vision systems, for example, in a robotic system.
Twórcy
autor
  • Institute of Automation and Robotics, Military University of Technology S. Kaliskiego 2, 00-908 Warsaw, Poland
autor
  • Institute of Automation and Robotics, Military University of Technology S. Kaliskiego 2, 00-908 Warsaw, Poland
autor
  • Institute of Simulation Sciences, De Montfort University The Gateway, Leicester LEI 9BH, England
Bibliografia
  • [1] Anagnou A., Blackledge J. M.: Research Report - Pattern Recognition using the Hough Transform. Science and Engineering Research Centre, De Montfort University, Leicester 1993.
  • [2] Ballard D. H., Brown С. M.: Computer Vision. Prentice-Hall, Englewood Cliffs, New York 1982.
  • [3] Ballard D. H.: Generalizing the Hough Transform to Detect Arbitrary Shapes. Readings in Computer Vision: Issues, Problems, Principles, and Paradigms. Los Altos, CA. 1987, pp. 714-725.
  • [4] Davies E. R.: Machine Vision: Theory, Algorithms, Practicalities. Academic press Ltd, 24/28 Oval Road, London NW1 7DX, United Kingdom 1990.
  • [5] Deans S. R.: Hough transform from the Radon transform. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 3, no. 2,1981, 185-188.
  • [6] Duda R. O., Hart P. E.: Use of the Hough Transformation to Detect Lines and Curves in Pictures. Comm. ACM., vol. 15, 1972, 11-15.
  • [7] Fu K. S., Gonzalez R. C., Lee C. S. G.: ROBOTICS: Control, Sensing, Vision, and Intelligence. McGraw-Hill, New York 1987.
  • [8] Hough P. V. C.: Method and means for recognizing complex patterns. U.S. Patent 3,069,654, Dec. 18, 1962.
  • [9] Illingworth J., Kittier J.: A survey of the Hough Transform. Computer Vision, Graphics and Image Processing 44, 1988, pp. 87-116.
  • [10] Jain A. K.: Fundamentals of Digital Image Processing. Prcntice-Hall, New Jersey 1989.
  • [11] Kiryati N., Eldar Y., Bruckstein A. M.: A probabilistic Hough transform. Pattern Recognition, vol. 24, no. 4, 1991, 303-316.
  • [12] Leavers V. F.: Shape Detection in Computer Vision Using the Hough Transform. Springer, London 1992.
  • [13] Li H., Lavin M. A., LeMaster R. J.: Fast Hough transform: a hierarchical approach. Computer Vision, Graphics, and Image Processing, vol. 36, 1986, 139- 161.
  • [14] McLaughlin R. A., A lder M. D.: Technical Report - The Hough Transform versus the UpWrite. Tech. Rep. 97/2, The University of Western Australia, Centre for Intelligent Information Processing Systems, Dept, of E.E. Eng., U.W.A., Stirling Hwy, Ncdlands W.A. 6907, Australia 1997, Available from http://ciips.ee.uwa.edu.au/Papers/Technical Reports/.
  • [15] Radon J.: Uber die Bestimmung von Funktionen durch ihre Integralwerte langs gewisser Mannigfaltigkeiten. Berichte Sachsische Akademie der Wissenschaften Leipzig, Math Phys KI., 69, pp 262-267, 1917.
  • [16] Żorski W., Foxon B„ Blackledgc J., Turner M.: Application of the Circle Hough Transform with a Clustering Technique to Segmentation of Digital Images. IMAGE PROCESSING II: Mathematical Methods, Algorithms & Applications, Horwood Publishing 2000, pp. 339-348.
  • [17] Żorski W., Foxon B., Blackledge J., Turner M.: Fingerprint and Iris Identification Method Based on the Hough Transform. Bulletin of the Institute of Automation and Robotics MUT, 15, 2001, pp. 43-54.
  • [18] Żorski W., Foxon B., Blackledge J., Turner M.: Irregular Colour Pattern Recognition Using the Hough Transform. Bulletin of the Institute of Automation and Robotics MUT, 15, 2001, pp. 27-42.
  • [19] Żorski W., Foxon B., Blackledge J., Turner M.: Irregular Pattern Recognition Using the Hough Transform. Machine Graphics & Vision, 9,2000, pp. 609-632.
  • [20] Żorski W., Murawski K.: Pattern Recognition in the Case of Small Differences. Proceedings of the 7th IEEE International Conference MM AR 2001, Vol.2, pp.1055-1060.
  • [21] Żorski W., Żak A., Turner M.: Hardware Implementation of the Hough Technique for Irregular Pattern Recognition. Proceedings of the 8th IEEE International Conference MMAR 2002, Vol.l, pp.561-566.
  • [22] Altera Corporation: System-On-a-Programmable-Chip Development Board User Guide. July 2000, ver. 1.1
  • [23] Żak A.: Design of a hardware implementation of the Hough Transform (written in Polish, Projekt sprzętowej realizacji transformaty Hougha). MSc thesis, Military University of Technology, Warsaw 2001.
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Bibliografia
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bwmeta1.element.baztech-article-BWA1-0002-0049
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