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Accurate segmentation of cracked body from three-dimensional (3D) industrial Computed Tomography (CT) images is an important step in the process of crack measurement and automatic recognition. In this paper we present a fast method for the segmentation of cracked body. The improved algorithm incorporates wavelet transform and Chan and Vese (C-V) model as key components. The 3D wavelet transform is applied for detecting rough edges. Then region growing is used to find a suitable region which contains cracked body. Based on the resulting volume data, 3D C-V model is used to capture the edges of cracked body. The improved method can locate rough regions by using wavelet modulus maxima, which not only reduces the amount of data C-V model processed, but also provides initial contour surface that can accelerate the convergence speed of C-V model. Experimental results illustrate our method can accurately detect the cracked surface, as well as give computational savings of segmentation which satisfy the demand of defects detection of industrial CT.
Date of Conference: 12-15 Aug. 2011