A Technology Of Image Segmentation Based On Cloud Theory

Image engineering is a subject that has been developed in recent years and it has many contents. According to the degree of abstract and the investigate methods, the research on it can be divided into three levels:image processing, image analysis and image comprehension. One of image processing goals is the pattern recognition, but the image segmentation and the survey are the pattern recognition work foundations. Image segmentation is an important and basic techniquein computer vision.It is a key technique in image understanding, imaging target recognition and tracking, robot vision, etc.Cloud theory is a theory dealing with uncertainty, including cloud model, Vir tualcloud,cloudoperations,cloudtransform,uncertaintyreasoning,etc.Cloudmodel is a model of the uncertain transition between a linguistic term of a qualitative concept and its numerical representation. Cloud model is the basis of cloud theory,it integrates the fuzziness and randomness of concept representation and the uncertain transition between qualitatives and quantitatives.Information processing technique developed from Cloud Theory, have advantage to process uncertainty event and describe uncertainty knowledge.Image segmentation is an intelligent process to partition image pixel based on image information and premise constraint conditons.An Image Segmentation algorithm based on Cloud Theory and region growing algorithm is proposed in the essay. First, it generated some cloud models that the method is to use Cloud Transformation transformed image, then it grows to obtain the final segmentation results by using the Ex of cloud model as seed points of region growing algorithm and using greatly determination law of Cloud Theory as the criteria of region growing algorithm. This segmentation method not only overcomes inappropriate selection of the region growing seed points and the region growing criteria from over-segmentation and less-segmentation, but also solves the segmentation difficulties on image'that has the vague demarcation and uncertain factors. Experimental results show that this method can accurately segment the target and is effective method of Image segmentation.