Extract the center of the coarse curve of binary image

I want to extract the center of a series of curves, as shown in the figure below, which looks roughly like the red line in the figure

Answer 1

[Image Analyst]

Try inverting the binary image and then using bwskel(). Demo attached.

[JH F]

I'm glad you could answer my questions. I've used skeletal extraction before, but there's always a problem: too many bone spurs (pictured). So many bone spurs will greatly hinder my subsequent treatment process. As a result, I would like to extract it into a smooth, segmented curve. Do you have any good ideas?

[Image Analyst]

Here's an attempt at it. Continue to refine it (because I can't spend the time to do the whole thing for you).

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;
fprintf('Beginning to run %s.m ...\n', mfilename);

%--------------------------------------------------------------------------------------------------------
%    READ IN IMAGE
folder = pwd;
baseFileName = 'fingerprint.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;
	end
end
grayImage = 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);
end
% Display the image.
hFig = figure;
subplot(4, 1, 1);
imshow(grayImage, []);
title('Original Grayscale Image', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
hFig.WindowState = 'maximized'; % May not work in earlier versions of MATLAB.
drawnow;

%--------------------------------------------------------------------------------------------------------
% Crop the image out of the screenshot
grayImage = grayImage(85:378, 9:1088);

%--------------------------------------------------------------------------------------------------------
%    SEGMENTATION
% Binarize the image
binaryImage = grayImage < 128;
% Display the binary image.
subplot(4, 1, 2);
cla;
imshow(binaryImage, []);
title('Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');
axis('on', 'image');

%--------------------------------------------------------------------------------------------------------
% Label the image so we can process each ride individually.
[labeledImage, numRegions] = bwlabel(binaryImage);
for k = 1 : numRegions
	fprintf('Processing ridge #%d of %d\n', k, numRegions);
	% Get this ridge
	thisRidge = ismember(labeledImage, k);
	
	%--------------------------------------------------------------------------------------------------------
	%    SKELETONIZATION
	% Now skeletonize
	skelImage = bwskel(thisRidge, 'MinBranchLength', 10); % First guess.  Strangely bwskel() doesn't seem to have any short spurs, no matter what MinBranchLength is.
	% skelImage = bwmorph(binaryImage, 'skel', inf); % First guess.  Will have short spurs.  Shouldn't use this, but going to just for the demo.
	% Display the original skeleton image, with annoying spurs
	subplot(4, 1, 3);
	imshow(skelImage, []);
	title('Original Skeleton Image', 'FontSize', fontSize, 'Interpreter', 'None');
	axis('on', 'image');
	drawnow;
	
	% First get the area of the skeleton and take half of it to get the MinBranchLength.
	% This should give use the longest spine path only, and get rid of all spurs (at least for THIS demo image).
	MinBranchLength = round(sum(skelImage(:))/2)
	% Now take the skeleton again using that min branch length we just computed.
	skelImage = bwskel(thisRidge, 'MinBranchLength', MinBranchLength);
	% Display the skeleton image.
	subplot(4, 1, 4);
	imshow(skelImage, []);
	title('Skeleton Image', 'FontSize', fontSize, 'Interpreter', 'None');
	axis('on', 'image');
	drawnow;
	
	% Get the coordinates of the skeleton
	[r, c] = find(skelImage);
	% Save them into a cell array (because they are all different sizes).
	x{k} = c;
	y{k} = r;
	% Overlay the skeleton on the original image.
	subplot(4, 1, 1);
	imshow(imoverlay(binaryImage, skelImage, 'r'));
	hold on;
	plot(c, r, 'r.', 'LineWidth', 4);
	title('Binary Image with Skeleton Overlaid', 'FontSize', fontSize, 'Interpreter', 'None');
	drawnow;
end

% Show final results.
hFig2 = figure;
imshow(grayImage);
title('Final Image', 'FontSize', fontSize, 'Interpreter', 'None');
axis('on', 'image');
drawnow;
hold on;
for k = 1 : numRegions
	thisx = x{k};
	thisy = y{k};
	plot(thisx, thisy, 'r.', 'LineWidth', 4);
end
fprintf('Done running %s.m ...\n', mfilename);
msgbox('Done!');

[JH F]

Ok, I will continue to improve it. Thank you very much for your answer.