Title :
A new color image segmentation algorithm based on watershed transformation
Author_Institution :
Depart.of Comput. Sci., Inst. for Syst. Anal. Acad. of Sci. of Russia, Russia
Abstract :
A new color segmentation method is presented in this paper. The method is specified for color images that have both large and small objects, and objects with both step and ramp edges. Scanned pages of color magazines and newspapers are the examples of this kind of images. Watershed transformation algorithm is the basis of the proposed method. Our method incorporates the original multi-scale analysis that allows to segment edges of different slope. This analysis uses fine-to-coarse strategy and prevents the already detected sharp edges from smoothing while moving to coarser scales. In the same time the introduced algorithm allows to detect ramp edges successfully at coarse scales. For fine scales we propose a special gradient operator and a modification of watershed transformation for small objects segmentation.
Keywords :
edge detection; image colour analysis; image segmentation; color image segmentation algorithm; fine-to-coarse strategy; multiscale analysis; sharp edge detection; watershed transformation algorithm; Algorithm design and analysis; Colored noise; Computer science; Gray-scale; Histograms; Image analysis; Image color analysis; Image edge detection; Image segmentation; Optical character recognition software;
Conference_Titel :
Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on
Print_ISBN :
0-7695-2128-2
DOI :
10.1109/ICPR.2004.1334317