Reduce density of points in ROI



P_reduced = reducepoly(P) reduces the density of points in array P. Specify P as an n-by-2 array of the form [x1 y1; ...; xn yn], where each row represents a point. For example, P could be the array returned by one of the ROI creation functions, such as drawfreehand or drawpolygon. reducepoly returns P_reduced, an n-by-2 array of points that is typically smaller that P.

reducepoly uses the Douglas-Peucker line simplification algorithm, removing points along a straight line and leaving only knickpoints (points where the line curves).

P_reduced = reducepoly(P,tolerance) reduces the density of points in array P, where tolerance specifies how much a point can deviate from a straight line. Specify tolerance in the range [0,1].


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Read an image into the workspace.

I = imread('coins.png');

Convert the image from a grayscale image to a binary image. The function for finding boundaries requires binary images.

bw = imbinarize(I);

Obtain the boundaries of all the coins in the binary image.

[B,L] = bwboundaries(bw,'noholes');

Plot the boundary for one of the coins over the original image.

hold on;
k = 1;
boundary = B{k};
plot(boundary(:,2), boundary(:,1), 'r', 'LineWidth', 2)
hold off;

Use reducepoly to reduce the number of points defining the coin boundary.

p = [boundary(:,2) boundary(:,1)];
tolerance = 0.02; % choose suitable tolerance
p_reduced = reducepoly(p,tolerance);

Compare the original polygon overlaid over the reduced polygon and see how well the shape defined by fewer vertices matches the original polygon.

hf = figure;
ha = axes('parent',hf,'box','on','Ydir','reverse');
axis equal
% Original data.
      'color',[1 0.5 0],'linestyle','-','linewidth',1.5,...
% Reduced data.
       'color',[0 0 1],'linestyle','-','linewidth',2,...
legend('Original points','Reduced points');
title('Douglas-Peucker algorithm');

Input Arguments

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Points to be reduced, specified as an n-by-2 array of the form [x1 y1; ...; xn yn]. Each row in the array defines a vertex in a polyline, polygon, or freehand ROI shape.

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64

Sensitivity of the reduction algorithm, specified as a numeric scalar in the range [0,1]. Increasing the tolerance increases the number of points removed. A tolerance value of 0 has a minimum reduction in points. A tolerance value of 1 results in maximum reduction in points, leaving only the end points of the line.

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64

Output Arguments

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Reduced data set, returned as a n-by-2 numeric array.

Data Types: double


The Douglas-Peucker line simplification algorithm recursively subdivides a shape looking to replace a run of points with a straight line. The algorithm checks that no point in the run deviates from the straight line by more than the value specified by tolerance.

Introduced in R2019b