A Parallel Adaptive Hierarchical Network Model for Image Segmentation
用于图像分割的并行自适应层次化网络模型

This paper describes a new parallel adaptive hierarchaical network model for image segmentation. The model consists of a layer for extracting local features and forming region in a parallel recursive way, a layer for adaptive statistcal clustering, and a layer for making decision under the guidance of global distribution features. The communication between these layers is realized by means of coorperation mechanism. With the automatic non-parameter clustering method, the un-surpervised image segmentation is completed by integrating the local gray feature with the global random distribution fealures. The model has been applied to the adaptive segmentation of outdoor natural scene image. Even though in the case of different enviroment, the experimental result is rather sa isfactory.