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  2. Euclidean distance - Wikipedia

    en.wikipedia.org/wiki/Euclidean_distance

    The distance from a point to a plane in three-dimensional Euclidean space [7] The distance between two lines in three-dimensional Euclidean space [8] The distance from a point to a curve can be used to define its parallel curve, another curve all of whose points have the same distance to the given curve. [9]

  3. Eigenface - Wikipedia

    en.wikipedia.org/wiki/Eigenface

    A nearest-neighbour method is a simple approach for finding the Euclidean distance between two vectors, where the minimum can be classified as the closest subject. [ 3 ] : 590 Intuitively, the recognition process with the eigenface method is to project query images into the face-space spanned by eigenfaces calculated, and to find the closest ...

  4. Scale-invariant feature transform - Wikipedia

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

    Finally, to avoid the expensive search required for finding the Euclidean-distance-based nearest neighbor, an approximate algorithm called the best-bin-first algorithm is used. [14] This is a fast method for returning the nearest neighbor with high probability, and can give speedup by factor of 1000 while finding nearest neighbor (of interest ...

  5. Medoid - Wikipedia

    en.wikipedia.org/wiki/Medoid

    This example shows how Euclidean distance will calculate the distance between objects to determine how similar the items are. Note that most text embeddings will be at least a few hundred dimensions instead of just two. Euclidean distance is a standard distance metric used to measure the dissimilarity between two points in a multi-dimensional ...

  6. Rigid transformation - Wikipedia

    en.wikipedia.org/wiki/Rigid_transformation

    In mathematics, a rigid transformation (also called Euclidean transformation or Euclidean isometry) is a geometric transformation of a Euclidean space that preserves the Euclidean distance between every pair of points. [1] [self-published source] [2] [3] The rigid transformations include rotations, translations, reflections, or any sequence of ...

  7. Metric space - Wikipedia

    en.wikipedia.org/wiki/Metric_space

    Wasserstein metrics measure the distance between two measures on the same metric space. The Wasserstein distance between two measures is, roughly speaking, the cost of transporting one to the other. The set of all m by n matrices over some field is a metric space with respect to the rank distance (,) = ().

  8. Line drawing algorithm - Wikipedia

    en.wikipedia.org/wiki/Line_drawing_algorithm

    Two rasterized lines. The colored pixels are shown as circles. Above: monochrome screening; below: Gupta-Sproull anti-aliasing; the ideal line is considered here as a surface. In computer graphics, a line drawing algorithm is an algorithm for approximating a line segment on discrete graphical media, such as pixel-based displays and printers.

  9. Color difference - Wikipedia

    en.wikipedia.org/wiki/Color_difference

    A very simple example can be given between the two colors with RGB values (0, 64, 0) ( ) and (255, 64, 0) ( ): their distance is 255. Going from there to (255, 64, 128) ( ) is a distance of 128. When we wish to calculate distance from the first point to the third point (i.e. changing more than one of the color values), we can do this: