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  2. Homomorphic filtering - Wikipedia

    en.wikipedia.org/wiki/Homomorphic_filtering

    According to figures one to four, we can see how homomorphic filtering is used for correcting non-uniform illumination in the image, and the image become clearer than the original. On the other hand, if we apply the high pass filter to the homomorphic filtered image, the edges of the images become sharper and the other areas become dimmer.

  3. Split and merge segmentation - Wikipedia

    en.wikipedia.org/wiki/Split_and_merge_segmentation

    Split and merge segmentation is an image processing technique used to segment an image.The image is successively split into quadrants based on a homogeneity criterion and similar regions are merged to create the segmented result.

  4. 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 ...

  5. Region growing - Wikipedia

    en.wikipedia.org/wiki/Region_growing

    Let g be an image formed by appending to each seed point in S all the 1-valued points in fo that are 8-connected to that seed point. Label each connected component in g with a different region label (e.g., 1, 2, 3, ...). This is the segmented image obtained by region growing.

  6. Image moment - Wikipedia

    en.wikipedia.org/wiki/Image_moment

    In image processing, computer vision and related fields, an image moment is a certain particular weighted average of the image pixels' intensities, or a function of such moments, usually chosen to have some attractive property or interpretation. Image moments are useful to describe objects after segmentation.

  7. Erosion (morphology) - Wikipedia

    en.wikipedia.org/wiki/Erosion_(morphology)

    An Introduction to Morphological Image Processing by Edward R. Dougherty, ISBN 0-8194-0845-X (1992) Morphological Image Analysis; Principles and Applications by Pierre Soille, ISBN 3-540-65671-5 (1999) R. C. Gonzalez and R. E. Woods, Digital image processing, 2nd ed. Upper Saddle River, N.J.: Prentice Hall, 2002.

  8. Local binary patterns - Wikipedia

    en.wikipedia.org/wiki/Local_binary_patterns

    Multi-block LBP: the image is divided into many blocks, a LBP histogram is calculated for every block and concatenated as the final histogram. Volume Local Binary Pattern(VLBP): [11] VLBP looks at dynamic texture as a set of volumes in the (X,Y,T) space where X and Y denote the spatial coordinates and T denotes the frame index. The neighborhood ...

  9. Watershed (image processing) - Wikipedia

    en.wikipedia.org/wiki/Watershed_(image_processing)

    This flooding process is performed on the gradient image, i.e. the basins should emerge along the edges. Normally this will lead to an over-segmentation of the image, especially for noisy image material, e.g. medical CT data. Either the image must be pre-processed or the regions must be merged on the basis of a similarity criterion afterwards.