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Morphological operators are used for post-processing to remove small false positives around the edges.

Morphological operators are applied to extract circular leaf patterns in different scales from the leaf images.

Road regions are segmented using average intensity values, and morphological operators are used for further processing.

Morphological operators are used for further processing to remove this unwanted road regions.

In this paper, starting from a brief historical overview of rank order filters and erosions/dilations in digital image processing, rank order based morphological operators are surveyed.

The multiscale properties of NSCT make this method flexible in extracting salient borderlines between feature regions, and the mathematical morphological operators are employed subsequently to deal with occasional broken filaments or over-segmentation.

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A novel set of color image morphological operators is proposed and is based on using a modified vector distance measure with an efficient preprocessing color pixel classification procedure.

After edge thresholding, the morphological operators were employed to obtain single-pixel edge curves, resulting in the final binarized edge image shown in Figure 4c.

In particular, in [4], a semi-automatic detection method based on morphological operators is used to locate the vesicles fusion in space and time.

A standardized combination of morphological operators was applied to fill holes and smooth the follow-up mask.

Rank order morphological operators have been designed to better cope with shape variations and noise than the corresponding operators with plain structuring elements.

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