Learning OpenCV 3 by Adrian Kaehler and Gary Bradski

Author:Adrian Kaehler and Gary Bradski
Language: eng
Format: mobi
Publisher: O'Reilly Media, Inc.
Published: 2016-12-27T16:00:00+00:00

The first difference is that FAST only uses the points on a ring around P. The second is that individual points on the ring are classified as either darker than P, lighter than P, or similar to P. This classification is done with a threshold t, such that the darker pixels are ones that are less bright than IP – t, the lighter pixels are ones that are more bright than IP + t, and the similar pixels are those that are in between IP – t and IP + t. Once this classification has been done, the FAST detector requires some number of contiguous points on the ring to be either all brighter or all darker than P. If the number of points on the ring is N, then the arc that contains only lighter or darker pixels must contain at least N/2 + 1 pixels (i.e., more than half the total number on the ring).

This algorithm is already very fast, but a moment’s thought will also reveal that this test permits a convenient optimization in which only four equidistant points are tested. In this case, if there is not at least a pair of consecutive points that are brighter or darker than P, then the point P cannot be a FAST feature. In practice this optimization greatly reduces the time required to search an entire image.

One difficulty with the algorithm as described so far is that it will tend to return multiple adjacent pixels all as corners. In Figure 16-16, for example, the pixel directly above P, among others, is also a FAST keypoint. In general this is not desirable.

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