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
Link To Document