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Author Zhang, Kaihua ♦ Zhang, Lei ♦ Song, Huihui ♦ Zhang, David
Source CiteSeerX
Content type Text
File Format PDF
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Re-initialization Free Level Set Evolution ♦ Reaction Diffusion ♦ Rd-lse Equation ♦ Costly Re-initialization Procedure ♦ Rd-lse Approach ♦ Real Image ♦ Variational Level ♦ Simple Finite Difference Method ♦ Two-step Splitting Method ♦ Lse Equation ♦ High Dimensional Level ♦ Rd-lse Model ♦ Good Performance ♦ Rd Method ♦ Novel Reaction-diffusion ♦ Pde-based Level ♦ Promising Experimental Result ♦ Implicit Active Contour ♦ Second Step ♦ Rd-lse Method Show ♦ Diffusion Equation ♦ Diffusion Term ♦ First Step ♦ Stable Numerical Solution ♦ Piecewise Constant Solution ♦ Boundary Anti-leakage
Abstract Abstract — This paper presents a novel reaction-diffusion (RD) method for implicit active contours, which is completely free of the costly re-initialization procedure in level set evolution (LSE). A diffusion term is introduced into LSE, resulting in a RD-LSE equation, to which a piecewise constant solution can be derived. In order to have a stable numerical solution of the RD based LSE, we propose a two-step splitting method (TSSM) to iteratively solve the RD-LSE equation: first iterating the LSE equation, and then solving the diffusion equation. The second step regularizes the level set function obtained in the first step to ensure stability, and thus the complex and costly re-initialization procedure is completely eliminated from LSE. By successfully applying diffusion to LSE, the RD-LSE model is stable by means of the simple finite difference method, which is very easy to implement. The proposed RD method can be generalized to solve the LSE for both variational level set method and PDE-based level set method. The RD-LSE method shows very good performance on boundary anti-leakage, and it can be readily extended to high dimensional level set method. The extensive and promising experimental results on synthetic and real images validate the effectiveness of the proposed RD-LSE approach.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article