Can anyone help me to find coordinates of end-point of attached handwritten image in Matlab.
MATLAB: How to find end point of handwritten character
Image Processing Toolboxmorphology
Related Solutions
Use bwskel() to get the longest spine. Then use bwmorph() to get the endpoints of the spine. Then use find() and sqrt() to get the straight line distance between the endpoints, then divide the two.
% This demo computes the tortuosity of a snake-like shape by dividing the actual longest spine distance by the straight line distance between the endpoints.
clc; % Clear the command window.
close all; % Close all figures (except those of imtool.)
clear; % Erase all existing variables. Or clearvars if you want.
workspace; % Make sure the workspace panel is showing.
format long g;format compact;fontSize = 15;%--------------------------------------------------------------------------------------------------------
% READ IN IMAGE
folder = pwd;baseFileName = 'worm.png';% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);% Check if file exists.
if ~exist(fullFileName, 'file') % The file doesn't exist -- didn't find it there in that folder.
% Check the entire search path (other folders) for the file by stripping off the folder.
fullFileNameOnSearchPath = baseFileName; % No path this time.
if ~exist(fullFileNameOnSearchPath, 'file') % Still didn't find it. Alert user.
errorMessage = sprintf('Error: %s does not exist in the search path folders.', fullFileName); uiwait(warndlg(errorMessage)); return; endend% Read in the image from disk. If storedColorMap is not empty, it's an indexed image with a stored colormap.
[grayImage, storedColorMap] = imread(fullFileName);if ~isempty(storedColorMap) grayImage = ind2rgb(grayImage, storedColorMap);end% Get the dimensions of the image.
% numberOfColorChannels should be = 1 for a gray scale image, and 3 for an RGB color image.
[rows, columns, numberOfColorChannels] = size(grayImage);if numberOfColorChannels > 1 % It's not really gray scale like we expected - it's color.
% Use weighted sum of ALL channels to create a gray scale image.
grayImage = rgb2gray(grayImage); % ALTERNATE METHOD: Convert it to gray scale by taking only the green channel,
% which in a typical snapshot will be the least noisy channel.
% grayImage = grayImage(:, :, 2); % Take green channel.
end% Display the image.
hFig = figure;subplot(1, 2, 1);imshow(grayImage, []);title('Original Grayscale Image', 'FontSize', fontSize, 'Interpreter', 'None');impixelinfo;hFig.WindowState = 'maximized'; % May not work in earlier versions of MATLAB.
drawnow;%--------------------------------------------------------------------------------------------------------% SEGMENTATION
% Binarize the image
binaryImage = imbinarize(grayImage);% Take the largest blob only.
binaryImage = bwareafilt(binaryImage, 1);% Fill holes, if any.
binaryImage = imfill(binaryImage, 'holes');% Display the binary image.
subplot(1, 2, 1);imshow(binaryImage, []);title('Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');axis('on', 'image');% Now skeletonize
skelImage = bwskel(binaryImage); % First guess. Will have short spurs.
% First get the area of the skeleton and take half of it to be the longest spine length.
% This will get rid of all spurs.
MinBranchLength = round(sum(skelImage(:))/2)% Now take the skeleton again using that min branch length we just computed.
skelImage = bwskel(binaryImage, 'MinBranchLength', MinBranchLength);% Display the skeleton image.
subplot(1, 2, 2);imshow(skelImage, []);title('Skeleton Image', 'FontSize', fontSize, 'Interpreter', 'None');axis('on', 'image');% Find the endpoints
endpointImage = bwmorph(skelImage, 'endpoints');[rows, columns] = find(endpointImage)% Draw a red line between them.
hold on;plot(columns, rows, 'r-', 'LineWidth', 2);% Find the spine length.
% (Would be more accurate to find the spine length by traversing it.)
spineLength = sum(skelImage(:))% Compute the straight line distance.
straightLineDistance = sqrt((columns(2) - columns(1))^2 + (rows(2) - rows(1))^2)% Compute the tortuosity
tortuosity = spineLength / straightLineDistancecaption = sprintf('Skeleton Image. Tortuosity = %f', tortuosity);title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
Try this:
clc; % Clear the command window.
close all; % Close all figures (except those of imtool.)
clear; % Erase all existing variables. Or clearvars if you want.
workspace; % Make sure the workspace panel is showing.
format long g;format compact;fontSize = 22;%--------------------------------------------------------------------------------------------------------
% READ IN IMAGE
folder = pwd;baseFileName = 'image.png';% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);% Check if file exists.
if ~exist(fullFileName, 'file') % The file doesn't exist -- didn't find it there in that folder.
% Check the entire search path (other folders) for the file by stripping off the folder.
fullFileNameOnSearchPath = baseFileName; % No path this time.
if ~exist(fullFileNameOnSearchPath, 'file') % Still didn't find it. Alert user.
errorMessage = sprintf('Error: %s does not exist in the search path folders.', fullFileName); uiwait(warndlg(errorMessage)); return; endendgrayImage = imread(fullFileName);% Get the dimensions of the image.
% numberOfColorChannels should be = 1 for a gray scale image, and 3 for an RGB color image.
[rows, columns, numberOfColorChannels] = size(grayImage);if numberOfColorChannels > 1 % It's not really gray scale like we expected - it's color.
% Use weighted sum of ALL channels to create a gray scale image.
grayImage = rgb2gray(grayImage); % ALTERNATE METHOD: Convert it to gray scale by taking only the green channel,
% which in a typical snapshot will be the least noisy channel.
% grayImage = grayImage(:, :, 2); % Take green channel.
end% Display the image.
subplot(2, 2, 1);imshow(grayImage, []);title('Original Grayscale Image', 'FontSize', fontSize, 'Interpreter', 'None');impixelinfo;hFig = gcf;hFig.WindowState = 'maximized'; % May not work in earlier versions of MATLAB.
drawnow;%--------------------------------------------------------------------------------------------------------% SEGMENTATION OF IMAGE
% Get a binary image of just the blob and not including the black background or the white surround.
mask = grayImage > 0 & grayImage < 255; %imbinarize(grayImage);
subplot(2, 2, 2);imshow(mask, []);impixelinfo;title('Initial Mask Image', 'FontSize', fontSize, 'Interpreter', 'None');impixelinfo;% Display histogram of image but only the image within the mask
subplot(2, 3, 4);histogram(grayImage(mask), 0:255);grid on;title('Histogram of gray image', 'FontSize', fontSize);% Now get the threshold
thresh = 255 * graythresh(grayImage(mask))% Put a red line there at the threshold
xline(thresh, 'Color', 'r', 'LineWidth', 2);% Get a binary image of the bright stuff
brightStuff = grayImage >= thresh & mask;subplot(2, 3, 5);imshow(brightStuff, []);impixelinfo;title('Bright Pixels in Region', 'FontSize', fontSize, 'Interpreter', 'None');impixelinfo;subplot(2, 3, 6);darkStuff = ~brightStuff & mask;imshow(darkStuff, []);impixelinfo;title('Dark Pixels in Region', 'FontSize', fontSize, 'Interpreter', 'None');impixelinfo;
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