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  2. Balanced histogram thresholding - Wikipedia

    en.wikipedia.org/wiki/Balanced_histogram...

    Like Otsu's Method [2] and the Iterative Selection Thresholding Method, [3] this is a histogram based thresholding method. This approach assumes that the image is divided in two main classes: The background and the foreground. The BHT method tries to find the optimum threshold level that divides the histogram in two classes. Original image ...

  3. Plotting algorithms for the Mandelbrot set - Wikipedia

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

    To get colorful images of the set, the assignment of a color to each value of the number of executed iterations can be made using one of a variety of functions (linear, exponential, etc.). One practical way, without slowing down calculations, is to use the number of executed iterations as an entry to a palette initialized at startup.

  4. 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 ...

  5. Sturges's rule - Wikipedia

    en.wikipedia.org/wiki/Sturges's_rule

    Sturges's rule [1] is a method to choose the number of bins for a histogram. Given observations, Sturges's rule suggests using ^ = + ⁡ bins in the histogram. This rule is widely employed in data analysis software including Python [2] and R, where it is the default bin selection method. [3]

  6. Scott's rule - Wikipedia

    en.wikipedia.org/wiki/Scott's_Rule

    Scott's rule is widely employed in data analysis software including R, [2] Python [3] and Microsoft Excel where it is the default bin selection method. [ 4 ] For a set of n {\displaystyle n} observations x i {\displaystyle x_{i}} let f ^ ( x ) {\displaystyle {\hat {f}}(x)} be the histogram approximation of some function f ( x ) {\displaystyle f ...

  7. Otsu's method - Wikipedia

    en.wikipedia.org/wiki/Otsu's_method

    An example image thresholded using Otsu's algorithm Original image. In computer vision and image processing, Otsu's method, named after Nobuyuki Otsu (大津展之, Ōtsu Nobuyuki), is used to perform automatic image thresholding. [1]

  8. Histogram - Wikipedia

    en.wikipedia.org/wiki/Histogram

    Smooth histogram for signals and images from a few samples; Histograms: Construction, Analysis and Understanding with external links and an application to particle Physics. A Method for Selecting the Bin Size of a Histogram; Histograms: Theory and Practice, some great illustrations of some of the Bin Width concepts derived above. Matlab ...

  9. scikit-image - Wikipedia

    en.wikipedia.org/wiki/Scikit-image

    scikit-image (formerly scikits.image) is an open-source image processing library for the Python programming language. [2] It includes algorithms for segmentation , geometric transformations, color space manipulation, analysis, filtering, morphology, feature detection , and more. [ 3 ]