A Convex Approach for Local Statistics Based Region Segmentation

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“A Convex Approach for Local Statistics Based Region Segmentation,” Chinese Journal of Electronics, vol. 21, no. 4, pp. 623-626, 2012,

Citation:

“A Convex Approach for Local Statistics Based Region Segmentation,” Chinese Journal of Electronics, vol. 21, no. 4, pp. 623-626, 2012,

“A Convex Approach for Local Statistics Based Region Segmentation,” Chinese Journal of Electronics, vol. 21, no. 4, pp. 623-626, 2012,

Citation:

“A Convex Approach for Local Statistics Based Region Segmentation,” Chinese Journal of Electronics, vol. 21, no. 4, pp. 623-626, 2012,

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A Convex Approach for Local Statistics Based Region Segmentation

Received Date: 2011-03-01
Rev Recd Date: 2012-04-01
Publish Date: 2012-10-25

Abstract

Abstract

A convex active contour model based on local image statistics is proposed in this paper. By assuming that the intensity distribution of the image pixels in a window is described by a Gaussian distribution, our model is able to segment images with intensity inhomogeneity. Due to the convexity of the proposed model, we introduce a dual formulation to solve the minimization problem and obtain a much efficient method. Experiments show that the segmentation results of the proposed method are similar to that of the non-convex method based on local statistics, but our method is much more efficient.

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References(16)

References

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