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Microsoft Word - bases for segmentation.docx; Author: Home: Software used: PScript5.dll Version 5.2.2: File change date and time: 03:48, 30 November 2016: Date and time of digitizing: 03:48, 30 November 2016: Conversion program: Acrobat Distiller 10.1.10 (Windows) Encrypted: no: Page size: 612 x 792 pts (letter) Version of PDF format: 1.5
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 ...
The random walker algorithm is an algorithm for image segmentation. In the first description of the algorithm, [1] a user interactively labels a small number of pixels with known labels (called seeds), e.g., "object" and "background". The unlabeled pixels are each imagined to release a random walker, and the probability is computed that each ...
to the end of the template code, making sure it starts on the same line as the code's last character. This category is for article-related templates that improve Wikipedia's use of Web semantics. For background information on the concept of Web semantics (meaningful markup, as opposed to pure presentation/display), see:
ITK is an open-source software toolkit for performing registration and segmentation. Segmentation is the process of identifying and classifying data found in a digitally sampled representation. Typically the sampled representation is an image acquired from such medical instrumentation as CT or MRI scanners. Registration is the task of aligning ...
Example video frames and their object co-segmentation annotations (ground truth) in the Noisy-ViDiSeg [1] dataset. Object segments are depicted by the red edge. In computer vision, object co-segmentation is a special case of image segmentation, which is defined as jointly segmenting semantically similar objects in multiple images or video ...
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Connected-component labeling (CCL), connected-component analysis (CCA), blob extraction, region labeling, blob discovery, or region extraction is an algorithmic application of graph theory, where subsets of connected components are uniquely labeled based on a given heuristic.