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Highlights from
Algorithm Development with MATLAB

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Algorithm Development with MATLAB

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21 May 2013 (Updated )

Demo files to go with recorded webinar.

Find Green Object

Find Green Object

This script reads in an image file and then attempts to find a green object in the image. It is designed to find one green ball and highlight that ball on the original image

Contents

Housekeeping

clear all; close all; clc;

Step 1: Read image into MATLAB

First we read the specified image from the file and bring it into MATLAB as a variable. We also display the image to ensure it is correct.

greenBall1 = imread('greenBall1.jpg');
t = imtool(greenBall1);
close(t);

Step 2: Identify Unique Characteristics of Object of Interest

Extract each color Next we using indexing to extract three 2D matrices from the 3D image data corresponding to the red, green, and blue components of the image.

r = greenBall1(:, :, 1);
g = greenBall1(:, :, 2);
b = greenBall1(:, :, 3);

View different color planes

figure, colormap gray
subplot(2,2,1),imagesc(r)
subplot(2,2,2),imagesc(g)
subplot(2,2,3),imagesc(b)

Calculate Green Then we perform an arithmetic operation on the matrices as a whole to try to create one matrix that represents an intensity of green.

justGreen = g - r/2 - b/2;
colorPlanesPlot(r,g,b,justGreen);
close all

Step 3: Isolate Object of Interest

Threshold the image Now we can set a threshold to separate the parts of the image that we consider to be green from the rest.

bw = justGreen > 50;
imagesc(bw);
colormap(gray);

Remove small unwanted objects We can use special functions provided by the Image Processing toolbox to quickly perform common image processing tasks. Here we are using BWAREAOPEN to remove groups of pixels less than 30.

ball1 = bwareaopen(bw, 30);
imagesc(ball1);

Step 4: Find center of green object

Now we are using REGIONPROPS to extract the centroid of the group of pixels representing the ball.

s  = regionprops(ball1, {'centroid','area'});
if isempty(s)
  error('No ball found!');
else
  [~, id] = max([s.Area]);
  hold on, plot(s(id).Centroid(1),s(id).Centroid(2),'wp','MarkerSize',20,'MarkerFaceColor','r'), hold off
  disp(['Center location is (',num2str(s(id).Centroid(1),4),', ',num2str(s(id).Centroid(2),4),')'])
end
Center location is (151.9, 138.2)

Step 5: Verify estimated location

Finally we will plot the center on the original image to clearly evaluate how well we have found the center.

imagesc(greenBall1);
hold on, plot(s(id).Centroid(1),s(id).Centroid(2),'wp','MarkerSize',20,'MarkerFaceColor','r'), hold off

Clean up

clear all; close all; clc

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