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  2. Pulse-coupled networks - Wikipedia

    en.wikipedia.org/wiki/Pulse-coupled_networks

    The Eckhorn model provided a simple and effective tool for studying small mammal’s visual cortex, and was soon recognized as having significant application potential in image processing. In 1994, Johnson adapted the Eckhorn model to an image processing algorithm, calling this algorithm a pulse-coupled neural network.

  3. Insight Segmentation and Registration Toolkit - Wikipedia

    en.wikipedia.org/wiki/Insight_Segmentation_and...

    ITK was developed with funding from the National Library of Medicine as an open resource of algorithms for analyzing the images of the Visible Human Project. ITK stands for The Insight Segmentation and Registration Toolkit. The toolkit provides leading-edge segmentation and registration algorithms in two, three, and more dimensions. ITK uses ...

  4. Connected-component labeling - Wikipedia

    en.wikipedia.org/wiki/Connected-component_labeling

    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.

  5. Point Cloud Library - Wikipedia

    en.wikipedia.org/wiki/Point_Cloud_Library

    The Point Cloud Library (PCL) is an open-source library of algorithms for point cloud processing tasks and 3D geometry processing, such as occur in three-dimensional computer vision. The library contains algorithms for filtering, feature estimation, surface reconstruction, 3D registration, [5] model fitting, object recognition, and segmentation ...

  6. Statistical region merging - Wikipedia

    en.wikipedia.org/wiki/Statistical_Region_Merging

    Thus, the resultant set will be 1.8, 3.2, 4.9, 5.2, 5.6, 9, 10. Note the result on SRM varies, based on the order in which the values are evaluated by the algorithm. A major use of SRM is in image processing where higher number color palettes in an image are converted into lower number palettes by merging the similar colors' palettes together ...

  7. Graph cuts in computer vision - Wikipedia

    en.wikipedia.org/wiki/Graph_cuts_in_computer_vision

    As applied in the field of computer vision, graph cut optimization can be employed to efficiently solve a wide variety of low-level computer vision problems (early vision [1]), such as image smoothing, the stereo correspondence problem, image segmentation, object co-segmentation, and many other computer vision problems that can be formulated in terms of energy minimization.

  8. Active contour model - Wikipedia

    en.wikipedia.org/wiki/Active_contour_model

    A simple elastic snake is defined by a set of n points for =, …,, the internal elastic energy term , and the external edge-based energy term .The purpose of the internal energy term is to control the deformations made to the snake, and the purpose of the external energy term is to control the fitting of the contour onto the image.

  9. Segmentation-based object categorization - Wikipedia

    en.wikipedia.org/wiki/Segmentation-based_object...

    Given an image D containing an instance of a known object category, e.g. cows, the OBJ CUT algorithm computes a segmentation of the object, that is, it infers a set of labels m. Let m be a set of binary labels, and let Θ {\displaystyle \Theta } be a shape parameter( Θ {\displaystyle \Theta } is a shape prior on the labels from a layered ...