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自动化学报 2009
Two-dimensional Extension of Minimum Error Threshold Segmentation Method for Gray-level Images
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Abstract:
One-dimensional minimum error thresholding method assumed that the histogram distributions of object and background are governed by a mixture Gaussian distribution. Considering the affects of noise and other factors on image quality, based on the assumption of a two-dimensional mixture Gaussian distribution, a two-dimensional expression of the minimum error thresholding method on the two-dimensional gray-level histogram is proposed. In order to improve the running speed, the fast recursive formulas are also given. Experimental results show that the two-dimensional minimum error thresholding method is a valuable image segmentation method, and can be well adapted to the images with noises and large variances between object and background.