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SURFPoints

Object for storing SURF interest points

Description

This object provides the ability to pass data between the detectSURFFeatures and extractFeatures functions. It can also be used to manipulate and plot the data returned by these functions. You can use the object to fill the points interactively. You can use this approach in situations where you might want to mix a non-SURF interest point detector with a SURF descriptor.

Creation

Syntax

points = SURFPoints(Location)
points = SURFPoints(location,Name,Value)

Description

example

points = SURFPoints(Location) constructs a SURFPoints object from an M-by-2 array of [x y] point coordinates, Location.

points = SURFPoints(location,Name,Value) sets properties using one or more name-value pairs. Enclose each property name in quotes. For example, points = SURFPoints('Metric',0.0)

Input Arguments

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Point coordinates, specified as an M-by-2 array. The Location input contains M number of [x y] points.

Properties

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Number of points held by the object, specified as a numeric value.

Point locations, specified as an M-by-2 array of [x y] point coordinates.

Scale at which the feature is detected, specified as a value greater than or equal to 1.6.

Strength of detected feature, specified as a numeric value. The BRISK algorithm uses a determinant of an approximated Hessian.

Orientation of the detected feature, specified as an angle, in radians. The angle is measured counter-clockwise from the X-axis with the origin specified by the Location property. Do not set this property manually. Rely instead, on the call to extractFeatures to fill in this value. The extractFeatures function modifies the default value of 0.0.The Orientation is mainly useful for visualization purposes.

Sign of the Laplacian determined during the detection process, specified as -1, 0, or 1. You can use this parameter to accelerate the feature matching process.

Blobs with identical metric values but different signs of Laplacian can differ by their intensity values. For example, a white blob on a blackground versus a black blob on a white background. You can use this parameter to quickly eliminate blobs that do not match.

For non-SURF detectors, this property is not relevant. For example, for corner features, you can simply use the default value of 0.

Object Functions

plotPlot points
isemptyDetermine if points object is empty
lengthNumber of stored points
selectStrongestSelect points with strongest metrics
sizeReturn the size of a points object
selectUniformSelect uniformly distributed subset of feature points

Examples

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Read in image.

    I = imread('cameraman.tif');

Detect SURF features.

    points = detectSURFFeatures(I);

Display location and scale for the 10 strongest points.

    strongest = points.selectStrongest(10);
    imshow(I); hold on;
    plot(strongest);

Display [x y] coordinates for the 10 strongest points on command line.

    strongest.Location
ans = 10x2 single matrix

  139.7482   95.9542
  107.4502  232.0347
  116.6112  138.2446
  105.5152  172.1816
  113.6975   48.7220
  104.4210   75.7348
  111.3914  154.4597
  106.2879  175.2709
  131.1298   98.3900
  124.2933   64.4942

Read in image.

    I = imread('cameraman.tif');

Detect SURF feature.

    points = detectSURFFeatures(I);

Display the last 5 points.

    imshow(I); hold on;
    plot(points(end-4:end));

Tips

Although SURFPoints may hold many points, it is a scalar object. Therefore, numel(surfPoints) always returns 1. This value may differ from length(surfPoints), which returns the true number of points held by the object.

References

[1] Bay, H., A. Ess, T. Tuytelaars, and L. Van Gool. “SURF:Speeded Up Robust Features.” Computer Vision and Image Understanding (CVIU).Vol. 110, No. 3, pp. 346–359, 2008.

Extended Capabilities

Introduced in R2011b