模版匹配定位跟踪

梦里梦外; 2022-09-11 10:28 70阅读 0赞

%% 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

%% 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;  
figure;  
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);  
figure;  
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.  
figure;  
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

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

![watermark_type_ZHJvaWRzYW5zZmFsbGJhY2s_shadow_50_text_Q1NETiBAZnBnYSZtYXRsYWI_size_16_color_FFFFFF_t_70_g_se_x_16][]

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