Level set segmentation depending on adaptive local information
Tiejun Yang, Lin Huang · 2010
A robust and efficient level set segmentation method using the energy in a reasonable range of segmentation dependent information (RSDI) is presented. A feature describing edges' illegibility, called the edges' blur descriptor, is first defined. Then it is used to compute RSDI adaptively and approximately. Some methods of segmentation dependent information localization (SDIL) utilizing a window function are discussed. The window size is determined by RSDI. We used the proposed method to improve the region-scalable fitting (RSF) method. Experiments show that it can choose RSDI effectively, and the segmentation accuracy and performance are superior to RSF method.