selectUniform

Select uniformly distributed subset of feature points

Syntax

pointsOut = selectUniform(points,N,imageSize)

Description

pointsOut = selectUniform(points,N,imageSize) returns N uniformly distributed points from pointsIn points of an image of size imageSize.

Examples

Select Uniformly Distributed Subset of KAZE Features

Detect and plot a subset of uniformly distributed KAZE features from an image.

Read an image.

im = imread('yellowstone_left.png');

Detect and display KAZE features.

points1 = detectKAZEFeatures(rgb2gray(im))

points1 = 
  6712x1 KAZEPoints array with properties:

       Location: [6712x2 single]
         Metric: [6712x1 single]
          Count: 6712
          Scale: [6712x1 single]
    Orientation: [6712x1 single]

subplot(1,2,1)
imshow(im)
hold on
plot(points1)
hold off
title('Original Points')

Select a uniformly distributed subset of points.

numPoints = 100;
points2 = selectUniform(points1,numPoints,size(im))

points2 = 
  100x1 KAZEPoints array with properties:

       Location: [100x2 single]
         Metric: [100x1 single]
          Count: 100
          Scale: [100x1 single]
    Orientation: [100x1 single]

subplot(1,2,2)
imshow(im)
hold on
plot(points2)
hold off
title('Uniformly Distributed Points')

Select A Uniformly Distributed Subset of Features From an Image

Load an image.

im = imread('yellowstone_left.png');

Detect many corners by reducing the quality threshold.

points1 = detectHarrisFeatures(rgb2gray(im), 'MinQuality', 0.05);

Plot image with detected corners.

subplot(1,2,1);
imshow(im);
hold on
plot(points1);
hold off
title('Original points');

Select a uniformly distributed subset of points.

numPoints = 100;
points2 = selectUniform(points1,numPoints,size(im));

Plot images showing original and subset of points.

subplot(1, 2, 2);
imshow(im);
hold on
plot(points2);
hold off
title('Uniformly distributed points');

Select A Uniformly Distributed Subset of Features From an Image

Load an image.

im = imread('yellowstone_left.png');

Detect many corners by reducing the quality threshold.

points1 = detectBRISKFeatures(rgb2gray(im), 'MinQuality', 0.05);

Plot image with detected corners.

subplot(1,2,1);
imshow(im);
hold on
plot(points1);
hold off
title('Original points');

Select a uniformly distributed subset of points.

numPoints = 100;
points2 = selectUniform(points1,numPoints,size(im));

Plot images showing original and subset of points.

subplot(1, 2, 2);
imshow(im);
hold on
plot(points2);
hold off
title('Uniformly distributed points');

Select A Uniformly Distributed Subset of Features From an Image

Load an image.

im = imread('yellowstone_left.png');

Detect and display SURF features.

points1 = detectSURFFeatures(rgb2gray(im));
subplot(1,2,1);
imshow(im);
hold on
plot(points1);
hold off
title('Original points');

Select a uniformly distributed subset of points.

numPoints = 100;
points2 = selectUniform(points1,numPoints,size(im));

Plot images showing original and subset of points.

subplot(1, 2, 2);
imshow(im);
hold on
plot(points2);
hold off
title('Uniformly distributed points');

Input Arguments

points — Points object

KAZEPoints object | CornerPoints object | BRISKPoints object | SURFPoints object | ORBPoints object

Points object, specified as a points object. The object contains information about the feature points detected in the input image. To obtain points, use the appropriate detect function.

N — Number of points

integer

Number of uniformly distributed points to select, specified as an integer.

imageSize — Size of image

2-element vector | 3-element vector

Size of image, specified as a 2-element vector for grayscale images or a 3-element vector for truecolor images.