Connected components, in a 2D image, are clusters of pixels with the same value, which are connected to each other through either 4-pixel, or 8-pixel connectivity. 4-pixel connectivity would group all pixels that contact each other on either of their four faces, while 8-pixel would group pixels that are connected along any face or corner. In 3D, your connectivity options, at least for rectangular pixels, are 6, 18, and 26 (faces, faces+edges, faces+edges+corners).
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Connected components, in a 2D image, are clusters of pixels with the same value, which are connected to each other through either 4-pixel, or 8-pixel connectivity. 4-pixel connectivity would group all pixels that contact each other on either of their four faces, while 8-pixel would group pixels that are connected along any face or corner. In 3D, your connectivity options, at least for rectangular pixels, are 6, 18, and 26 (faces, faces+edges, faces+edges+corners).
If it's at a all applicable, I'd like to to take moment recommend you take a look at our newly released image processing software at http://MIPAR.us. We offer several user-friendly ways to segment, and then rapidly calculate and display the connected components of 2D and 3D segmentations. Thanks for the question!
In text detection, connected component plays a vital role. Each connected component ensures that the underlying pixels forms a single character. This helps in identification of characters.
Connected-component labeling is used in computer vision to detect connected regions in binary digital images, although color images and data with higher dimensionality can also be processed. When integrated into an image recognition system or human-computer interaction interface, connected component labeling can operate on a variety of information.Blob extraction is generally performed on the resulting binary image from a thresholding step, but it can be applicable to gray-scale and color images as well. Blobs may be counted, filtered, and tracked.