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Application of the circle Hough transform with a clustering technique to segmentation of digital images

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EN
Abstrakty
EN
The paper presents the problem of segmenting digital images. The presented method is based on the circle Hough transform. A fundamental element of this method is the clustering technique. The technique simplifies the application of Hough transform to segmentation tasks as well as accelerates the calculations considerably.
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autor
  • Cybernetics Faculty, Military University of Technology, 01-489 Warsaw, S. Kaliskiego 2, Poland
autor
  • School of Computing and Matchematical Sciences. De montfort University. The Gateway, Leicester LE1 9BH, England
  • The paper presents the problem of segmenting digital images. The presented method is based on the circle Hough transform. A fundamental element of this method is the clustering technique. The technique simplifies the application of Hough transform to segmentation tasks as well as accelerates the calculations considerably.
autor
  • The paper presents the problem of segmenting digital images. The presented method is based on the circle Hough transform. A fundamental element of this method is the clustering technique. The technique simplifies the application of Hough transform to segmentation tasks as well as accelerates the calculations considerably.
Bibliografia
  • [1] Anagnou A., Blackledge J. M., Research Report - Pattern Recognition using the Hough Transform. Sciences and Engineering Research Centre, De Montfort University, Leicester 1993.
  • [2] Anil K., Jain, Fundamentals of Digital Image Processing. Prentice-Hall, New Jersey 1989.
  • [3] Arbushi V., Cantoni V., Musso G., Recognition and Location of Mechanical Parts Using Hough Transform. Pitman, London 1983.
  • [4] Ballard D. H., Brown C. M., Computer Vision. Prentice-Hall, Englewood Cliffs, New York 1982.
  • [5] Fu K S., Gonzalez R. C., Lee C. S. G., ROBOTICS: Control, Sensing, Vision, and Intelligence McGraw-Hill, New York 1987.
  • [6] Hall E. L., Computer Image Processing and Recognition. Academic Press, New York 1979
  • [7] Hu Y., Dennis T. J., Textured Image Segmentation by Context Enhanced Clustering. IEE Proceedings-Vision Image and Signal Processing, 6, 1994, pp. 413-421.
  • [8] Illingworth J., Kittier J., A survey of the Hough Transform. Computer Vision, Graphics and Image Processing 44, 1988, pp. 87-116.
  • [9] Kwiatkowski W., Dyfuzyfikacja transformaty Hougha Biuletyn IAiR WAT, 5. 1996, pp. 3-20.
  • [10] Kwiatkowski W., Pomiar przemieszczenia obiektu na obrazie rastrowym z wykorzystaniem przekształcenia DFT. Biuletyn WAT, 4, 1994, pp 47-60.
  • [11] Kwiatkowski W., Zastosowanie techniki Hougha przetwarzania obrazów do pomiaru zmiany położenia obiektu na obrazie rastrowym. Biuletyn WAT. 4. 1994, pp. 33-46.
  • [12] Leavers V. F., Shape Detection in Computer Vision Using the Hough Transform. Springer, London 1992.
  • [13] Li H., Lavin M. A., Le Master R. J., Fast Hough Transform. Computer Vision, Graphics and Image Processing, 36, 1986, pp. 139-161.
  • [14] McLaughlin R. A., Alder 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, Nedlands W.A. 6907, Australia, Available from http://ciips.ee.uwa.edu.au/Papers/Technical_Reports/, 1997.
  • [15] Tou J. T., González R. C., Pattern recognition principles. Addison-Wesley Publishing Company, London 1974.
  • [16] Application of the Circle Hough Transform with a clustering technique digital images Machine Graphics & Vision, 5, 1996, pp. 111-121.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BWA2-0002-0066
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