How to smooth rough edges along a binary image
Hey, I'm trying to mark out the tips and bases of each finger on the following image I binarized the image using the following piece of code a = imread('img235.jpg'); a = rgb2gray(a); msk = a > 30; props = regionprops(logical(msk), 'Area'); allAreas = sort([props.Area]); msk = bwareaopen(msk, 25); msk = imclearborder(msk); bw2 = bwareafilt(msk,1); BW2 = imfill(bw2,'holes'); to obtain this image: I next formed a boundary around the image using bwboundaries and marked out the peaks and valleys of the fingers, and I'm trying to estimate where the edge of the little finger is located by finding the distance between the tip of the little finger and the valley between the little finger and the valley between the little finger and the ring finger. My problem is that because the boundary between the little finger tip and the valley is smoother than the boundary on the other side of the little finger, I do not obtain a good estimate for the location of the base of the little finger because the jagged edges on this end of the boundary of the little finger mean there are a greater number of pixels along the boundary and the boundary is overall longer than it should be. My question is how do I smooth out these jags/irregularities along the boundary? I would ideally like to obtain a smooth boundary across the entire hand, such as along the smooth edge of the little finger shown in the image above.
Prashant Kumar answered .
2025-11-20
There are several ways. You could simply blur the image with conv2() and re-threshold
windowSize = 51; kernel = ones(windowSize) / windowSize ^ 2; blurryImage = conv2(single(binaryImage), kernel, 'same'); binaryImage = blurryImage > 0.5; % Rethreshold
Or you could use a Savitzky-Golay filter along with bwboundaries() to smooth out the coordinates, then use poly2mask() if you need to turn the coordinates into an image again. See demo.
% Demo to smooth a 2D outline (boundary) of a blob using Savitzky-Golay filters.
function savitky_golay_filter_smooth_outline()
clc; % Clear the command window.
close all; % Close all figures (except those of imtool.)
workspace; % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 25;
% Read in a standard MATLAB gray scale demo image.
button = menu('Use which demo image?', 'CameraMan', 'Moon', 'MRI', 'Glass', 'Pout');
thresholdValue = 125;
if button == 1
baseFileName = 'cameraman.tif';
thresholdValue = 75;
elseif button == 2
baseFileName = 'moon.tif';
thresholdValue = 25;
elseif button == 3
baseFileName = 'mri.tif';
thresholdValue = 33;
elseif button == 4
baseFileName = 'glass.webp';
thresholdValue = 125;
else
baseFileName = 'pout.tif';
thresholdValue = 125;
end
%===============================================================================
% Read in a standard MATLAB gray scale demo image.
folder = fileparts(which('cameraman.tif')); % Determine where demo folder is (works with all versions).
% baseFileName = 'moon.tif';
% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);
% Check if file exists.
if ~exist(fullFileName, 'file')
% File doesn't exist -- didn't find it there. Check the search path for it.
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.
% numberOfColorBands should be = 1.
[rows, columns, numberOfColorBands] = size(grayImage);
if numberOfColorBands > 1
% It's not really gray scale like we expected - it's color.
% Convert it to gray scale by taking only the green channel.
grayImage = grayImage(:, :, 2); % Take green channel.
end
% Display the original gray scale image.
subplot(2, 3, 1);
imshow(grayImage, []);
axis on;
title('Original Grayscale Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0 0 1 1]);
% Give a name to the title bar.
set(gcf, 'Name', 'Demo by ImageAnalyst', 'NumberTitle', 'Off')
% Let's compute and display the histogram.
[pixelCount, grayLevels] = imhist(grayImage);
subplot(2, 3, 2);
bar(grayLevels, pixelCount); % Plot it as a bar chart.
grid on;
title('Histogram of original image', 'FontSize', fontSize, 'Interpreter', 'None');
xlabel('Gray Level', 'FontSize', fontSize);
ylabel('Pixel Count', 'FontSize', fontSize);
xlim([0 grayLevels(end)]); % Scale x axis manually.
% Threshold the image
binaryImage = grayImage > thresholdValue;
% Get rid of holes in the blobs.
binaryImage = imfill(binaryImage, 'holes');
%---------------------------------------------------------------------------
% Extract the largest area using our custom function ExtractNLargestBlobs().
numberToExtract = 1;
biggestBlob = ExtractNLargestBlobs(binaryImage, numberToExtract);
%---------------------------------------------------------------------------
% Display the binary image.
subplot(2, 3, 3);
imshow(biggestBlob, []);
title('Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Get the boundaries.
% First, display the original gray scale image.
subplot(2, 3, 4);
imshow(grayImage, []);
axis image; % Make sure image is not artificially stretched because of screen's aspect ratio.
hold on;
% Now get the boundaries.
boundaries = bwboundaries(biggestBlob);
numberOfBoundaries = size(boundaries, 1);
for k = 1 : numberOfBoundaries
thisBoundary = boundaries{k};
plot(thisBoundary(:,2), thisBoundary(:,1), 'g', 'LineWidth', 2);
end
hold off;
caption = sprintf('%d Outlines, from bwboundaries()', numberOfBoundaries);
title(caption, 'FontSize', fontSize);
axis on;
firstBoundary = boundaries{1};
% Get the x and y coordinates.
x = firstBoundary(:, 2);
y = firstBoundary(:, 1);
% Now smooth with a Savitzky-Golay sliding polynomial filter
windowWidth = 45
polynomialOrder = 2
smoothX = sgolayfilt(x, polynomialOrder, windowWidth);
smoothY = sgolayfilt(y, polynomialOrder, windowWidth);
% First, display the original gray scale image.
subplot(2, 3, 5);
imshow(grayImage, []);
axis image; % Make sure image is not artificially stretched because of screen's aspect ratio.
hold on;
plot(smoothX, smoothY, 'r-', 'LineWidth', 2);
grid on;
title('Smoothed Boundary', 'FontSize', fontSize);
%==============================================================================================
% Function to return the specified number of largest or smallest blobs in a binary image.
% If numberToExtract > 0 it returns the numberToExtract largest blobs.
% If numberToExtract < 0 it returns the numberToExtract smallest blobs.
% Example: return a binary image with only the largest blob:
% binaryImage = ExtractNLargestBlobs(binaryImage, 1);
% Example: return a binary image with the 3 smallest blobs:
% binaryImage = ExtractNLargestBlobs(binaryImage, -3);
function binaryImage = ExtractNLargestBlobs(binaryImage, numberToExtract)
try
% Get all the blob properties. Can only pass in originalImage in version R2008a and later.
[labeledImage, numberOfBlobs] = bwlabel(binaryImage);
blobMeasurements = regionprops(labeledImage, 'area');
% Get all the areas
allAreas = [blobMeasurements.Area];
if numberToExtract > length(allAreas);
% Limit the number they can get to the number that are there/available.
numberToExtract = length(allAreas);
end
if numberToExtract > 0
% For positive numbers, sort in order of largest to smallest.
% Sort them.
[sortedAreas, sortIndexes] = sort(allAreas, 'descend');
elseif numberToExtract < 0
% For negative numbers, sort in order of smallest to largest.
% Sort them.
[sortedAreas, sortIndexes] = sort(allAreas, 'ascend');
% Need to negate numberToExtract so we can use it in sortIndexes later.
numberToExtract = -numberToExtract;
else
% numberToExtract = 0. Shouldn't happen. Return no blobs.
binaryImage = false(size(binaryImage));
return;
end
% Extract the "numberToExtract" largest blob(a)s using ismember().
biggestBlob = ismember(labeledImage, sortIndexes(1:numberToExtract));
% Convert from integer labeled image into binary (logical) image.
binaryImage = biggestBlob > 0;
catch ME
errorMessage = sprintf('Error in function ExtractNLargestBlobs().\n\nError Message:\n%s', ME.message);
fprintf(1, '%s\n', errorMessage);
uiwait(warndlg(errorMessage));
end