• DocumentCode
    3323931
  • Title

    Comparing color edge detection and segmentation methods

  • Author

    Allen, J. Thomas ; Huntsberger, Terrance

  • Author_Institution
    Dept. of Comput. Sci., Furman Univ., Greenville, SC, USA
  • fYear
    1989
  • fDate
    9-12 Apr 1989
  • Firstpage
    722
  • Abstract
    The authors report the results of a controlled comparative study of four proposed methods for extracting boundaries in static images using color information. The first two techniques are, more properly speaking, edge-detection methods. These include the adaptation of the Hueckel operator to color images by R. Nevatia (1977) and the DOOG (difference of offset Gaussians) operator proposed by R. Young (1985, 1986). The latter two methods are examples of region-based segmentation. These include the adaptation of R. Ohlander et al. (1978), region splitting by Y. Ohta et al. (1980), and the fuzzy c-means segmentation and edge-detection methods of T.L. Huntsberger et al. (1985). The methods are compared using both simulated, controlled images as well as a variety of natural scene images. Images with various levels of randomly additive noise provide some indication of the degradation of performance of these methods under noisy conditions
  • Keywords
    picture processing; boundaries extraction; color images; colour edge detection; colour segmentation; fuzzy c-means segmentation; noisy conditions; performance degradation; picture processing; randomly additive noise; region splitting; region-based segmentation; static images; Biological system modeling; Computer science; Displays; Gaussian processes; Histograms; Image edge detection; Least squares approximation; Lighting; Machine vision; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Southeastcon '89. Proceedings. Energy and Information Technologies in the Southeast., IEEE
  • Conference_Location
    Columbia, SC
  • Type

    conf

  • DOI
    10.1109/SECON.1989.132495
  • Filename
    132495