GraphCut 2D


From wikipedia: Graph partitioning methods can effectively be used for image segmentation. In these methods, the image is modeled as a weighted, undirected graph. Usually a pixel or a group of pixels are associated with nodes and edge weights define the (dis)similarity between the neighborhood pixels. The graph (image) is then partitioned according to a criterion designed to model "good" clusters. Each partition of the nodes (pixels) output from these algorithms are considered an object segment in the image. see also (Graph Cuts and Efficient N-D Image Segmentation (Boykov et. al)):

Input Ports

  1. Type: Data
    Images and Seed Labeling (optional)

Output Ports

  1. Type: Data
    Image BitType


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KNIME Image Processing


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