New Segmentation Technique Based on Clustering of Graph Theory
Jingyu Yang · 2008
In image segmentation,the traditional method of graph theory clustering is sensitive to salt pepper noise and fuzzy edges,produces much pseudo cutting-set and computational complexity.So,an improved approach is proposed in the paper.First,a newly classifying method is proposed,which is based on the same gray values,rather than the commonly used each pixel.Then,the definition of weight function is improved,which considers the spatial relation between pixel and regions,not only the gray values and position relation between two pixels.Experimental results show that the new method can automatically segment images with fewer parameters to other contrast algorithms,and the required storage space and realized complexity get satisfied improvement to the traditional algorithm's.