Title :
Level set segmentation depending on adaptive local information
Author :
Tie-Jun, Yang ; Lin, Huang
Author_Institution :
Coll. of Inf. Sci. & Eng., Guilin Univ. of Technol., Guilin, China
Abstract :
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.
Keywords :
image restoration; image segmentation; set theory; RSDI; adaptive local information; edges blur descriptor; level set segmentation; region scalable fitting method; segmentation dependent information localization; window function; Variable speed drives; image segmentation; level set; segmentation dependent information localization;
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Electronic_ISBN :
978-1-4244-7237-6
DOI :
10.1109/ICCASM.2010.5620397