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  2. Minimum spanning tree-based segmentation - Wikipedia

    en.wikipedia.org/wiki/Minimum_spanning_tree...

    A minimum spanning tree (MST) is a minimum-weight, cycle-free subset of a graph's edges such that all nodes are connected. In 2004, Felzenszwalb introduced a segmentation method [4] based on Kruskal's MST algorithm. Edges are considered in increasing order of weight; their endpoint pixels are merged into a region if this doesn't cause a cycle ...

  3. Split and merge segmentation - Wikipedia

    en.wikipedia.org/wiki/Split_and_merge_segmentation

    Download QR code; Print/export ... Split and merge segmentation is an image processing technique ... segmentation of a gray scale image using matlab. [2 ...

  4. Statistical region merging - Wikipedia

    en.wikipedia.org/wiki/Statistical_Region_Merging

    There are several implementations available of SRM for color image segmentation: Java, [3] Matlab, [4] Python, [5] and a demo applet. [3] SRM has been used in many image applications, like ClickRemoval [6] and Volume Catcher. [7]

  5. GrabCut - Wikipedia

    en.wikipedia.org/wiki/Grabcut

    GrabCut is an image segmentation method based on graph cuts.. Starting with a user-specified bounding box around the object to be segmented, the algorithm estimates the color distribution of the target object and that of the background using a Gaussian mixture model.

  6. Random walker algorithm - Wikipedia

    en.wikipedia.org/wiki/Random_walker_algorithm

    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".

  7. CVIPtools - Wikipedia

    en.wikipedia.org/wiki/CVIPtools

    CVIP has the ability to read various image formats, including TIFF, PNG, GIF, JPEG, BMP, and RAW formats. It supports standard image processing functions, image compression, restoration, logical and arithmetical operations between images, contrast manipulation, image sharpening, frequency transformation, edge detection, segmentation, and geometric transformations.

  8. Image segmentation - Wikipedia

    en.wikipedia.org/wiki/Image_segmentation

    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 ...

  9. 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.