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Moving edges are detected from, applying edge segment-based matching by making use of.
Moving edges are detected from by eliminating background edges using and.
Some of the moving edges are also removed during postprocessing to filter out noisy edge segments.
After detection, moving edges are grouped together, where each group represents a moving object [20].
Detected moving edges are utilized along with watershed algorithm for extracting video object plane (VOP) with more accurate boundary.
Still the detected moving edges are scattered and deviate from the ground truth of the moving object as shown in Figure 1(i).
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Each group of moving edges is used to generate the region of interest (ROI).
Rectangular bounding box of moving edges is used to determine the ROI of moving object for segmentation.
As for the quantitative evaluation, the accuracy of detected moving edges is determined, where ground truth is obtained by extracting moving edges manually.
This localisation at the moving edge is also supported by live-cell-imaging of pEGFP-SPRR1B transfected keratinocytes, further accentuating the presence of SPRR in membrane ruffles at the migrating front of the cell (Movie S1).
Moving edges in are detected by making use of these three DT images, where is used first to detect the coarse moving edge list, and later on and are used for noise filtering.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com