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  2. Histogram of oriented gradients - Wikipedia

    en.wikipedia.org/.../Histogram_of_oriented_gradients

    The histogram of oriented gradients (HOG) is a feature descriptor used in computer vision and image processing for the purpose of object detection.The technique counts occurrences of gradient orientation in localized portions of an image.

  3. 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 ...

  4. Viola–Jones object detection framework - Wikipedia

    en.wikipedia.org/wiki/Viola–Jones_object...

    Value: oriented gradients of pixel intensities Further, the design of Haar features allows for efficient computation of f w , b ( I ) {\displaystyle f_{w,b}(I)} using only constant number of additions and subtractions, regardless of the size of the rectangular features, using the summed-area table .

  5. Scale-invariant feature transform - Wikipedia

    en.wikipedia.org/wiki/Scale-invariant_feature...

    An orientation histogram with 36 bins is formed, with each bin covering 10 degrees. Each sample in the neighboring window added to a histogram bin is weighted by its gradient magnitude and by a Gaussian-weighted circular window with a that is 1.5 times that of the scale of the keypoint. The peaks in this histogram correspond to dominant ...

  6. GLOH - Wikipedia

    en.wikipedia.org/wiki/GLOH

    GLOH (Gradient Location and Orientation Histogram) is a robust image descriptor that can be used in computer vision tasks. It is a SIFT-like descriptor that considers more spatial regions for the histograms. An intermediate vector is computed from 17 location and 16 orientation bins, for a total of 272-dimensions.

  7. Talk:Histogram of oriented gradients - Wikipedia

    en.wikipedia.org/wiki/Talk:Histogram_of_oriented...

    2 Orientation binning gradient image selection criteria for ... 1 comment. 4 Needs an Example Image. 1 comment. Toggle the table of contents. Talk: Histogram of ...

  8. Plotting algorithms for the Mandelbrot set - Wikipedia

    en.wikipedia.org/wiki/Plotting_algorithms_for...

    The top row is a series of plots using the escape time algorithm for 10000, 1000 and 100 maximum iterations per pixel respectively. The bottom row uses the same maximum iteration values but utilizes the histogram coloring method. Notice how little the coloring changes per different maximum iteration counts for the histogram coloring method plots.

  9. Adjoint state method - Wikipedia

    en.wikipedia.org/wiki/Adjoint_state_method

    The adjoint state method is a numerical method for efficiently computing the gradient of a function or operator in a numerical optimization problem. [1] It has applications in geophysics, seismic imaging, photonics and more recently in neural networks. [2] The adjoint state space is chosen to simplify the physical interpretation of equation ...