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- Title
New Local Thresholding Method for Soil Images by Minimizing Grayscale Intra-Class Variance.
- Authors
Hapca, Simona M.; Houston, Alasdair N.; Oten, Wilfred; Baveye, Philippe C.
- Abstract
Recent advances in imaging techniques ofer the possibility of visualizing the three-dimensional structure of soils at very ine scales. To make use of such informaion, a thresholding process is commonly implemented to separate the image into solid paricles and pores. Despite the mulitude of thresholding algorithms available, their performance is being challenged by the complexity of the soil structure. Experience shows that, to improve thresholding performance, exising methods require signiicant input from a skilled operator, making the thresholding subjecive. In this context, this aricle proposes a new, operator-independent thresholding technique based on the analysis of the intraclass grayscale variance. The method extends the well-established Otsu technique, by applying irst a preclassiicaion of the voxels corresponding to the solid phase. Then, a threshold value is determined through minimizaion of the intraclass variance of the unclassiied voxels. The method was implemented globally, then locally for a range of window sizes, with the opimal window size selected as that for which the standardized grayscale variances of the two voxel populaions are equal. Results on the three-dimensional soil images invesigated suggest that the proposed method performs noiceably beter than Otsu’s method, and in paricular is robust enough to variaions in image contrast and soil structure. Tested on a syntheic image, the new method produces a misclassiicaion of only 2% of voxels, compared to 4.9% with Otsu’s method. These results suggest that the proposed method can be very useful in the analysis of images of a variety of heterogeneous media, including soils.
- Publication
Vadose Zone Journal, 2013, Vol 12, Issue 3, p1
- ISSN
1539-1663
- Publication type
Article
- DOI
10.2136/vzj2012.0172