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  2. Taxicab geometry - Wikipedia

    en.wikipedia.org/wiki/Taxicab_geometry

    Taxicab geometry or Manhattan geometry is geometry where the familiar Euclidean distance is ignored, and the distance between two points is instead defined to be the sum of the absolute differences of their respective Cartesian coordinates, a distance function (or metric) called the taxicab distance, Manhattan distance, or city block distance.

  3. Chebyshev distance - Wikipedia

    en.wikipedia.org/wiki/Chebyshev_distance

    On a chessboard, where one is using a discrete Chebyshev distance, rather than a continuous one, the circle of radius r is a square of side lengths 2r, measuring from the centers of squares, and thus each side contains 2r+1 squares; for example, the circle of radius 1 on a chess board is a 3×3 square.

  4. Admissible heuristic - Wikipedia

    en.wikipedia.org/wiki/Admissible_heuristic

    Two different examples of admissible heuristics apply to the fifteen puzzle problem: Hamming distance; Manhattan distance; The Hamming distance is the total number of misplaced tiles. It is clear that this heuristic is admissible since the total number of moves to order the tiles correctly is at least the number of misplaced tiles (each tile ...

  5. Similarity measure - Wikipedia

    en.wikipedia.org/wiki/Similarity_measure

    Manhattan distance is commonly used in GPS applications, as it can be used to find the shortest route between two addresses. [citation needed] When you generalize the Euclidean distance formula and Manhattan distance formula you are left with the Minkowski distance formulas, which can be used in a wide variety of applications. Euclidean distance

  6. Norm (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Norm_(mathematics)

    The distance derived from this norm is called the Manhattan distance or distance. The 1-norm is simply the sum of the absolute values of the columns. In contrast, ∑ i = 1 n x i {\displaystyle \sum _{i=1}^{n}x_{i}} is not a norm because it may yield negative results.

  7. Distance transform - Wikipedia

    en.wikipedia.org/wiki/Distance_transform

    A distance transformation. Usually the transform/map is qualified with the chosen metric. For example, one may speak of Manhattan distance transform, if the underlying metric is Manhattan distance. Common metrics are: Euclidean distance; Taxicab geometry, also known as City block distance or Manhattan distance. Chebyshev distance

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    mail.aol.com

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  9. Sum of absolute differences - Wikipedia

    en.wikipedia.org/wiki/Sum_of_absolute_differences

    To calculate the SAD values, the absolute value of the difference between each corresponding pair of pixels is used: the difference between 2 and 2 is 0, 4 and 1 is 3, 7 and 8 is 1, and so forth. Calculating the values of the absolute differences for each pixel, for the three possible template locations, gives the following: