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A known problem of the watershed method is over-segmentation.
(e) Result obtained by the watershed method with a threshold of 40.
(d) Result obtained by the watershed method with a threshold of 20.
The disadvantage of the watershed method is that the different types of images need different thresholds.
The segmentation function adopted by the watershed method is gradient [9].
The watershed method that is applicable to nonspecific image type is also unsupervised [9, 17].
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Additionally, curves from proposed and watershed methods are depicted.
Table 3 F-measures and computational time of the noisy images conducted by the proposed and watershed methods.
Amongst the unsupervised methods, the proposed method can segment the most objects, and also has a significantly higher F-measure than the E-GVF snake and watershed methods.
The analysis procedure adopting image contrast enhancement, noise removal and particle separation by threshold and "watershed" methods was applied to 2μm × 2μm AFM images of the Au droplets.
Figure 10 reveals that both the proposed and watershed methods demonstrate the capability of fully segmenting objects inside another object and overlapping objects but the E-GVF snake method cannot be applied in these pictures.
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