• DocumentCode
    595100
  • Title

    Multi scale multi structuring element top-hat transform for linear feature detection

  • Author

    Xiangzhi Bai ; Fugen Zhou ; Bindang Xue

  • Author_Institution
    Image Process. Center, Beihang Univ., Beijing, China
  • fYear
    2012
  • fDate
    11-15 Nov. 2012
  • Firstpage
    1920
  • Lastpage
    1923
  • Abstract
    To efficiently detect all the possible linear features, a multi scale multi structuring element top-hat transform based algorithm is proposed in this paper. The algorithm is divided into two parts: the multi scale multi structuring element top-hat transform and postprocessing. In the multi scale multi structuring element top-hat transform, multi scales of multi structuring elements with increasing sizes are used by the top-hat transform to extract the useful information of linear features. In the post processing, the detected linear feature regions are binarized, firstly. Then, the small noise regions are removed. After that, the final linear feature regions are thinned to form the final binary detected linear features. Experimental results show that, the proposed algorithm could efficiently detect all the possible linear features of different types of images and could be widely used for linear feature detection in different applications.
  • Keywords
    feature extraction; information retrieval; wavelet transforms; binary detected linear feature; image post processing; linear feature detection; linear feature information extraction; linear feature region; multiscale multistructure element top-hat transform; Algorithm design and analysis; Detectors; Feature extraction; Image edge detection; Noise; Pattern recognition; Transforms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition (ICPR), 2012 21st International Conference on
  • Conference_Location
    Tsukuba
  • ISSN
    1051-4651
  • Print_ISBN
    978-1-4673-2216-4
  • Type

    conf

  • Filename
    6460531