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In digital image processing and computer vision, image segmentation is the process of partitioning a digital image into multiple image segments, also known as image regions or image objects (sets of pixels). The goal of segmentation is to simplify and/or change the representation of an image into something that is more meaningful and easier to ...
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GrowCut is an interactive segmentation algorithm. It uses Cellular Automaton as an image model. Automata evolution models segmentation process. Each cell of the automata has some label (in case of binary segmentation - 'object', 'background' and 'empty'). During automata evolution some cells capture their neighbours, replacing their labels.
Image segmentation strives to partition a digital image into regions of pixels with similar properties, e.g. homogeneity. [1] The higher-level region representation simplifies image analysis tasks such as counting objects or detecting changes, because region attributes (e.g. average intensity or shape [2]) can be compared more readily than raw pixels.
For image segmentation, the matrix W is typically sparse, with a number of nonzero entries (), so such a matrix-vector product takes () time. For high-resolution images, the second eigenvalue is often ill-conditioned , leading to slow convergence of iterative eigenvalue solvers, such as the Lanczos algorithm .
A one-dimension example of scale-space segmentation. A signal (black), multi-scale-smoothed versions of it (red), and segment averages (blue) based on scale-space segmentation The dendrogram corresponding to the segmentations in the figure above. Each "×" identifies the position of an extremum of the first derivative of one of 15 smoothed ...
The American College of Gastroenterology also notes that IBS symptoms can vary in severity from person to person and that women are nearly twice as likely to have IBS than men – though it is not ...
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