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  2. Harris corner detector - Wikipedia

    en.wikipedia.org/wiki/Harris_corner_detector

    If we use Harris corner detector in a color image, the first step is to convert it into a grayscale image, which will enhance the processing speed. The value of the gray scale pixel can be computed as a weighted sums of the values R, B and G of the color image, {,,}, where, e.g.,

  3. Histogram matching - Wikipedia

    en.wikipedia.org/wiki/Histogram_matching

    It has a probability density function p r (r), where r is a grayscale value, and p r (r) is the probability of that value. This probability can easily be computed from the histogram of the image by = Where n j is the frequency of the grayscale value r j, and n is the total number of pixels in the image.

  4. OpenCV - Wikipedia

    en.wikipedia.org/wiki/OpenCV

    OpenCV (Open Source Computer Vision Library) is a library of programming functions mainly for real-time computer vision. [2] Originally developed by Intel, it was later supported by Willow Garage, then Itseez (which was later acquired by Intel [3]).

  5. Histogram equalization - Wikipedia

    en.wikipedia.org/wiki/Histogram_equalization

    For example, if applied to 8-bit image displayed with 8-bit gray-scale palette it will further reduce color depth (number of unique shades of gray) of the image. Histogram equalization will work the best when applied to images with much higher color depth than palette size, like continuous data or 16-bit gray-scale images.

  6. ImageJ - Wikipedia

    en.wikipedia.org/wiki/ImageJ

    It can read many image file formats, including TIFF, PNG, GIF, JPEG, BMP, DICOM, and FITS, as well as raw formats. ImageJ supports image stacks , a series of images that share a single window, and it is multithreaded , so time-consuming operations can be performed in parallel on multi-CPU hardware.

  7. Otsu's method - Wikipedia

    en.wikipedia.org/wiki/Otsu's_method

    hists is a 2D-histogram of grayscale value and neighborhood average grayscale value pair. total is the number of pairs in the given image.it is determined by the number of the bins of 2D-histogram at each direction. threshold is the threshold obtained.

  8. Maximally stable extremal regions - Wikipedia

    en.wikipedia.org/wiki/Maximally_stable_extremal...

    Given a source image, if a sequence of thresholded result images is generated where each image corresponds to an increasing threshold t, first a white image would be seen, then 'black' spots corresponding to local intensity minima will appear then grow larger. A maximally stable extremal region is found when size of one of these black areas is ...

  9. Thresholding (image processing) - Wikipedia

    en.wikipedia.org/wiki/Thresholding_(image...

    The simplest thresholding methods replace each pixel in an image with a black pixel if the image intensity , is less than a fixed value called the threshold , or a white pixel if the pixel intensity is greater than that threshold. In the example image on the right, this results in the dark tree becoming completely black, and the bright snow ...