An Improved Snake Algorithm Using Local Curvature


The KIPS Transactions:PartB , Vol. 15, No. 6, pp. 501-506, Dec. 2008
10.3745/KIPSTB.2008.15.6.501,   PDF Download:

Abstract

The classical snake algorithm has a problem in detecting the boundary of an object with deep concavities. While the GVF method can successfully detect boundary concavities, it consumes a lot of time computing the energy map. In this paper, we propose an algorithm to reduce the computation time and improve performance in detecting the boundary of an object with high concavity. We define the degree of complexity of object boundary as the local curvature. If the value of the local curvature is greater than a threshold value, new snake points are added. Simulation results on several different test images show that our method performs well in detecting object boundary and requires less computation time.


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Cite this article
[IEEE Style]
J. H. Lee, W. S. Choi, J. W. Jang, "An Improved Snake Algorithm Using Local Curvature," The KIPS Transactions:PartB , vol. 15, no. 6, pp. 501-506, 2008. DOI: 10.3745/KIPSTB.2008.15.6.501.

[ACM Style]
Jung Ho Lee, Wan Sok Choi, and Jong Whan Jang. 2008. An Improved Snake Algorithm Using Local Curvature. The KIPS Transactions:PartB , 15, 6, (2008), 501-506. DOI: 10.3745/KIPSTB.2008.15.6.501.