Method of the region growing image segmentation based on cloud theory
Jin Zhang · Electronic Instrumentation Customers · 2012
To deal with the selection of seed points and uncertainty information problems,this paper proposes a region growing based on cloud theory image segmentation method.Firstly,we use the global information access to the seed image point,specifically the cloud transform is generated by the intersection of the normal cloud model as a growth area of the seed point,with great determination principle as the region during the growth of the growth criterion,and then the region is transformed from quantitative pixel set to qualitative concept by backward cloud algorithm,and cloud synthesis algorithm is realized to merge the two adjacent regions,finally completion of the uncertainty based on region growing image segmentation.Experiments show that the method can be better than other methods of dealing with the uncertainty of the image information,and obtained good experimental results.