GRABCUT INTERACTIVE FOREGROUND EXTRACTION USING ITERATED GRAPH CUTS PDF

Segmented image, returned as binary image of the same size as the label matrix L. Tips For double and single images, grabcut assumes the range of the image to be [0 1]. For uint16, int16, and uint8 images, grabcut assumes the range to be the full range for the given data type. For grayscale images, the size of L , foremask , and backmask must match the size of the image A. For color and multi-channel images, L, foremask, and backmask must be 2-D arrays with the first two dimensions identical to the first two dimensions of the image A.

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Segmented image, returned as binary image of the same size as the label matrix L. Tips For double and single images, grabcut assumes the range of the image to be [0 1]. For uint16, int16, and uint8 images, grabcut assumes the range to be the full range for the given data type.

For grayscale images, the size of L , foremask , and backmask must match the size of the image A. For color and multi-channel images, L, foremask, and backmask must be 2-D arrays with the first two dimensions identical to the first two dimensions of the image A. Algorithms The algorithm treats all subregions fully or spatially outside the ROI mask as belonging to the background. To get an optimal segmentation, make sure the object to be segmented is fully contained within the ROI, surrounded by a small number of background pixels.

Do not mark a subregion of the label matrix as belonging to both the foreground mask and the background mask. If a region of the label matrix contains pixels belonging to both the foreground mask and background mask, the algorithm effectively treats the region as unmarked.

The algorithm assumes all subregions outside the region of interest belong to the background. Marking one of these subregions as belonging to foreground or background mask has no effect on the resulting segmentation.

References [1] Rother, C. Kolmogorov, and A. See Also.

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图像分割之(三)从Graph Cut到Grab Cut

An algorithm was needed for foreground extraction with minimal user interaction, and the result was GrabCut. How it works from user point of view? Initially user draws a rectangle around the foreground region foreground region should be completely inside the rectangle. Then algorithm segments it iteratively to get the best result. In that case, user need to do fine touch-ups.

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图割论文阅读笔记:“GrabCut” — Interactive Foreground Extraction using Iterated Graph Cuts

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