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  2. Image registration - Wikipedia

    en.wikipedia.org/wiki/Image_registration

    Knowing the correspondence between a number of points in images, a geometrical transformation is then determined to map the target image to the reference images, thereby establishing point-by-point correspondence between the reference and target images. [3] Methods combining intensity-based and feature-based information have also been developed ...

  3. Hough transform - Wikipedia

    en.wikipedia.org/wiki/Hough_transform

    Example 1. For each data point, a number of lines are plotted going through it, all at different angles. These are shown here in different colours. The Hough transform accumulates contributions from all pixels in the detected edge. To each line, a support line exists which is perpendicular to it and which intersects the origin. In each case ...

  4. Harris corner detector - Wikipedia

    en.wikipedia.org/wiki/Harris_corner_detector

    The Harris corner detector is a corner detection operator that is commonly used in computer vision algorithms to extract corners and infer features of an image. It was first introduced by Chris Harris and Mike Stephens in 1988 upon the improvement of Moravec's corner detector. [1]

  5. Generalised Hough transform - Wikipedia

    en.wikipedia.org/wiki/Generalised_Hough_transform

    The problem of finding the object (described with a model) in an image can be solved by finding the model's position in the image. With the generalized Hough transform, the problem of finding the model's position is transformed to a problem of finding the transformation's parameter that maps the model into the image.

  6. 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]).

  7. Circle Hough Transform - Wikipedia

    en.wikipedia.org/wiki/Circle_Hough_Transform

    The circle Hough Transform (CHT) is a basic feature extraction technique used in digital image processing for detecting circles in imperfect images. The circle candidates are produced by “voting” in the Hough parameter space and then selecting local maxima in an accumulator matrix.

  8. Canny edge detector - Wikipedia

    en.wikipedia.org/wiki/Canny_edge_detector

    The edge direction angle is rounded to one of four angles representing vertical, horizontal, and the two diagonals (0°, 45°, 90°, and 135°). An edge direction falling in each color region will be set to a specific angle value, for instance, θ in [0°, 22.5°] or [157.5°, 180°] maps to 0°.

  9. Kernel (image processing) - Wikipedia

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

    Corner pixels are extended in 90° wedges. Other edge pixels are extended in lines. Wrap The image is conceptually wrapped (or tiled) and values are taken from the opposite edge or corner. Mirror The image is conceptually mirrored at the edges. For example, attempting to read a pixel 3 units outside an edge reads one 3 units inside the edge ...