基于视觉显著模型和图割的图像分割方法分析.docx

Abstract
Image segmentation is a puter vision processing technology, which is the foundation of pattern recognition and image analysis. Effective and reasonable image segmentation can extract valid information as much as possible, so that a higher level of image understanding es possible. With the development and application puter, image segmentation has been widely used in the medical, transportation, industrial automation, video image processing. All in all, the image segmentation has important research significance, image segmentation, good or bad, will directly affect the subsequent image processing.
First, describes monly used current image segmentation algorithm, pare their advantages and disadvantages. Focuses on the visual saliency model and graph-based image segmentation method. Visual saliency model can quickly find out the significant regions in the image, but can not accurately cut the salient region pletely from the image. Graph-based image segmentation method, which is based on energy minimization framework, has quick segmentation speed and good segmentation results, but only in the case of human interaction, it can realize its advantages. Combining with the advantage of the visual saliency model, presented an image segmentation method based on visual saliency model and graph cuts. It uses visual saliency model to get the saliency regions in the image, which are used as initial conditions in the later segmentation. It not only maintains the fast speed of graph-based segmentation, and also achieves an automatic segmentation by using visual saliency model.
Through a large number of experiments, obtained more satisfactory binations, which may be affecting the performance of the method. At the same time, compared to mon graph-based algorithm, obtained a fully automatic segmentation , as well as had a good segmentation performance and fast segmentation speed in the condition of a similar segmentation results.
Key words: Visual Saliency Model, Graph Cuts