• DocumentCode
    3349367
  • Title

    Improved multi-scale and structuring element morphological detection in the log CT image

  • Author

    Yu, Lei ; Qi, Dawei

  • Author_Institution
    Coll. of Sci., Northeast Forestry Univ., Harbin
  • fYear
    2008
  • fDate
    21-24 Sept. 2008
  • Firstpage
    1248
  • Lastpage
    1253
  • Abstract
    Mathematical morphology is a new subject established based on rigorous mathematical theories. In the basis of set theory, mathematical morphology is used for image processing, analysing and comprehending. It is a powerful tool in the geometric morphological analysis and description. It has become a new theory in the digital image processing field. Moreover, it has deep influence on the image processing theory and technology. Edge is the basic feature in the medical image. It involves a lot of valuable target information of boundary, which is used for image processing, target identifying and image filtering. The mathematical morphology is an effective theory used to locate the image edge. In the paper multi-scale and structuring element in mathematical morphology is used to detect log CT image with defect, and provides a new method in log defect recognition.
  • Keywords
    computerised tomography; image recognition; mathematical morphology; medical image processing; digital image processing; geometric morphological analysis; geometric morphological description; image analysis; log CT image detection; log defect recognition; mathematical morphology; medical image; set theory; Biomedical imaging; Computed tomography; Digital images; Image analysis; Image edge detection; Image processing; Information filtering; Information filters; Morphology; Set theory; Computed tomography; Edge detection; Image processing; Mathematical morphology; Multi-scale and structuring element;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cybernetics and Intelligent Systems, 2008 IEEE Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4244-1673-8
  • Electronic_ISBN
    978-1-4244-1674-5
  • Type

    conf

  • DOI
    10.1109/ICCIS.2008.4670747
  • Filename
    4670747