DocumentCode
1845313
Title
C-V Level Set Model Based on the Gaussian Laplace Operator
Author
Jian-Ping Wang ; Yi-bin Lu ; Guang-cheng Cai ; De-an Wu
Author_Institution
Fac. of Sci., Kunming Univ. of Sci. & Technol. of China, Kunming, China
fYear
2013
fDate
21-23 June 2013
Firstpage
906
Lastpage
909
Abstract
The traditional Chan-Vese (C-V) model is sensitive to noise and inaccurate positioning of the edges in an image. This paper proposes a C-V model based on the Gaussian Laplace operator. By smoothing the image, the Gaussian smoothing function can reduce noise on the image segmentation. The Laplace operator can detect zero crossing points, and then determine the edge positions of the image. The experiments show that the proposed algorithm can achieve good segmentation effect.
Keywords
Gaussian processes; Laplace transforms; edge detection; image denoising; image segmentation; C-V level set model; Chan-Vese model; Gaussian Laplace operator; Gaussian smoothing function; Laplace operator; image edge position; image segmentation; image smoothing; noise reduction; zero crossing point detection; Capacitance-voltage characteristics; Deformable models; Image edge detection; Image segmentation; Laplace equations; Level set; Mathematical model; C-V model; Laplace operator; image segmentation; level set;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational and Information Sciences (ICCIS), 2013 Fifth International Conference on
Conference_Location
Shiyang
Type
conf
DOI
10.1109/ICCIS.2013.243
Filename
6643159
Link To Document