How to bridge some nearest unconnected image?

Hi all. I am focus on the filament recognition. Obviously, the initial work is the object detection. As the filament is long and thin, the detection result is discontinuous. A filament may have some small fragments. So I want to bridge these fragment into a large one.
Any suggestion to this issue are appreciated.

 Accepted Answer

You could first try morphological closing with imclose(). Or try edge linking ( http://www.csse.uwa.edu.au/~pk/Research/MatlabFns/#edgelink). Where did you upload your image to?

6 Comments

Thank you for your reminder. Just do the morphological closing with imclose() is not enough for my question. So does the edgelink. The image link is http://t1.qpic.cn/mblogpic/578e4d5f542ff85d5448/2000.jpg
There are a filament in the image with a small gap. I want to eliminate this gap.
Copy the image link to browser.If click it directly, it may does not work.
What does "not enough" mean? You can make the kernel huge if you want to close nearly any gap, though with changes in the outline shape. Otherwise you'll have to do something like find all pixels in each blob, find the two that are closest to each other in the two blobs, and draw a line with imline(). I have a demo for burning a line into a binary image with imline if you're interested.
@IA, I would be interested in imlineburn as well.
See this script:
% Demo to write an ellipse and a line into the overlay of an image,
% and then to burn those overlays into the image.
%----- Initializing steps -----
% Clean up
clc;
clear all;
close all;
workspace; % Display the workspace panel.
hasIPT = license('test', 'image_toolbox');
if ~hasIPT
% User does not have the toolbox installed.
message = sprintf('Sorry, but you do not seem to have the Image Processing Toolbox.\nDo you want to try to continue anyway?');
reply = questdlg(message, 'Toolbox missing', 'Yes', 'No', 'Yes');
if strcmpi(reply, 'No')
% User said No, so exit.
return;
end
end
% Display images to prepare for the demo.
monochromeImage = imread('pout.tif');
subplot(2, 4, 1);
imshow(monochromeImage);
title('Original Image');
subplot(2, 4, 2);
imshow(monochromeImage);
title('Original Image with ellipse in overlay');
subplot(2, 4, 5);
imshow(monochromeImage);
title('Original Image');
subplot(2, 4, 6);
imshow(monochromeImage);
title('Original Image with line in overlay');
set(gcf, 'units','normalized','outerposition',[0 0 1 1]); % Maximize figure.
set(gcf,'name','Image Analysis Demo','numbertitle','off')
%----- Burn ellipse into image -----
% Create elliptical mask, h, as an ROI object over the second image.
subplot(2, 4, 2);
hEllipse = imellipse(gca,[10 10 50 150]); % Second argument defines ellipse shape and position.
% Create a binary image ("mask") from the ROI object.
binaryImage = hEllipse.createMask();
% Display the ellipse mask.
subplot(2, 4, 3);
imshow(binaryImage);
title('Binary mask of the ellipse');
% Let's try to add some text. (Doesn't work)
% hText = text(50, 100, 'Line of Text');
% textMask = hText.createMask();
% binaryImage = binaryImage & textMask;
% imshow(binaryImage);
% Burn ellipse into image by setting it to 255 wherever the mask is true.
monochromeImage(binaryImage) = 255;
% Display the image with the "burned in" ellipse.
subplot(2, 4, 4);
imshow(monochromeImage);
title('New image with ellipse burned into image');
%----- Burn line into image -----
burnedImage = imread('pout.tif');
% Create line mask, h, as an ROI object over the second image in the bottom row.
subplot(2, 4, 6);
hLine = imline(gca,[10 100],[10 100]); % Second argument defines line endpoints.
% Create a binary image ("mask") from the ROI object.
binaryImage2 = hLine.createMask();
% Display the line mask.
subplot(2, 4, 7);
imshow(binaryImage2);
title('Binary mask of the line');
% Burn line into image by setting it to 255 wherever the mask is true.
burnedImage(binaryImage2) = 255;
% Display the image with the "burned in" line.
subplot(2, 4, 8);
imshow(burnedImage);
title('New image with line burned into image');

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