Hi Prashan,
I understand your query regarding a program with which you can scan the image, compare them and find the perimeters individually. Below are the steps that can help you in getting started assuming you have access to the images stored in a database and can retrieve them using MATLAB.
- Use MATLAB's database toolbox to connect to your database and retrieve the images.
- Convert the image to binary and use edge detection to find boundaries and calculate the perimeter of detected edges.
Below is the sample code:
% Step 1: Connect to the database and retrieve images
conn = database('your_database_name', 'username', 'password');
sqlquery = 'SELECT image_column FROM your_table';
curs = exec(conn, sqlquery);
curs = fetch(curs);
close(curs);
close(conn);
% Assuming the images are stored as binary blobs, convert them to MATLAB images
images = cell(size(curs.Data, 1), 1);
for i = 1:length(images)
images{i} = imread(curs.Data{i});
end
% Step 2: Calculate the perimeters
perimeters = zeros(length(images), 1);
for i = 1:length(images)
img = images{i};
% Convert to grayscale if necessary
if size(img, 3) == 3
img = rgb2gray(img);
end
% Convert to binary image
bw = imbinarize(img);
% Find edges
edges = edge(bw, 'Canny');
% Calculate perimeter
perimeters(i) = sum(edges(:));
end
% Step 3: Compare perimeters
disp('Perimeters of the images:');
disp(perimeters);
% Example comparison (e.g., difference between first two images)
if length(perimeters) >= 2
perimeter_diff = abs(perimeters(1) - perimeters(2));
fprintf('Difference between the perimeters of the first two images: %f\n', perimeter_diff);
end
For more understanding about database toolbox in MATLAB, refer to the following documentation:
And for edge detection refer to the following documentation:
Hope that helps!
