DocumentCode
1945211
Title
A Nonparametric Approach for Active Contours
Author
Ozertem, Umut ; Erdogmus, Deniz
Author_Institution
Oregon Health & Sci. Univ., Portland
fYear
2007
fDate
12-17 Aug. 2007
Firstpage
1407
Lastpage
1410
Abstract
Active contours are commonly used in many image segmentation applications. There are different active contour definitions, but all active contour definitions in the literature use parametric forms to determine the shape priors or adjust the weighting of internal and external forces acting on the active contour. However, the evaluation or estimation of the optimal values of these parameters is impossible in a general sense, and the algorithms are run with different parameters until a satisfactory result is obtained. To get rid of this exhaustive parameter search, we approach the same problem in a nonparametric way to translate the problem of seeking good values of these unknown parameters into seeking for a good density estimate. We tested the proposed method and compared with earlier approaches and obtained better results.
Keywords
image segmentation; search problems; active contours; exhaustive parameter search; image segmentation; nonparametric approach; Active contours; Image edge detection; Image processing; Image segmentation; Kernel; Neural networks; Object recognition; Shape; Testing; Video coding;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2007. IJCNN 2007. International Joint Conference on
Conference_Location
Orlando, FL
ISSN
1098-7576
Print_ISBN
978-1-4244-1379-9
Electronic_ISBN
1098-7576
Type
conf
DOI
10.1109/IJCNN.2007.4371164
Filename
4371164
Link To Document