Image segmentation is a chief and basic issue in the field of image analysis as well as pattern recognition. Meanwhile, it is also the classical puzzle in image processing. And the watershed transform is a powerful morphological tool for image segmentation. But its short-coming is to cause over-segmentation. Therefore, labeling watershed algorithm has been presented in this paper. Firstly, a bilateral filtering is applied to smooth the original image, so it can reduce part of noise. Secondly, according to the characteristics of the ore image the distance transform and morphological reconstruction are used to realize labeling watershed transformation on this basis. Finally, segmentation result is obtained by using an improved method of labeling watershed algorithm. The experimental result shows that the method can reduce over-segmentation more efficiently, with a precision of more than 80%.
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