Title :
A Nonparametric Approach for Active Contours
Author :
Ozertem, Umut ; Erdogmus, Deniz
Author_Institution :
Oregon Health & Sci. Univ., Portland
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;
Conference_Titel :
Neural Networks, 2007. IJCNN 2007. International Joint Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
978-1-4244-1379-9
Electronic_ISBN :
1098-7576
DOI :
10.1109/IJCNN.2007.4371164