Title :
An improved GVF snake model and its application to linear feature extraction from SAR images
Author :
Deng, Xin-Ping ; He, Chu ; Sun, Hong
Author_Institution :
Signal Process. Lab., Wuhan Univ., Wuhan, China
Abstract :
In this paper, an improved GVF snake model that allows controllable snakes is proposed. Two kinds of extern constraint forces are exploited in the model. The first one can pin specified points on the snake and determine the basic shape of a snake. The second one avoids generating ears during curve evolution. It ensures that the curves are smooth and won´t grow in a wrong direction. The improved snakes are employed to close gaps in linear feature extraction since they can fixes the connection points during the deformation and provide smooth linking curves rather than straight lines. The experimental results of ridge (and ravine) extraction and road extraction from real SAR images increase the correctness and quality of extracted results.
Keywords :
feature extraction; gradient methods; radar imaging; synthetic aperture radar; GVF snake model; SAR image; curve evolution; gradient vector flow; linear feature extraction; ridge extraction; road extraction; smooth linking curve; Detectors; Ear; Feature extraction; Image edge detection; Joining processes; Pixel; Roads; gradient vector flow (GVF); linear feature extraction; snake; sythetic apeture radar (SAR);
Conference_Titel :
Signal Processing (ICSP), 2010 IEEE 10th International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-5897-4
DOI :
10.1109/ICOSP.2010.5655726