Fill the lines of incomplete triangles and form complete triangle.

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I have a smoothed image which consists of 10 - 15 incomplete triangles (looks like triangles but few lines are not connected). I want to connect those lines and form a complete triangle and display the image. I have tried using houghlines but I am not able to complete those triangles. I am using MATLAB R2018a. I have attached an example of image I am trying up with this code:
% Apply edge detection to detect edges
edgeImage = edge(binaryImage, 'Canny');
% Apply line detection to detect line segments
lines = houghlines(edgeImage);
% Group line segments into triangles
triangleGroup = groupTriangleLines(lines);
% Display the image with joined lines
hold on;
% Draw the joined lines on the image
for i = 1:numel(triangleGroup)
triangle = triangleGroup(i).lines;
for j = 1:size(triangle, 1)
xy = [triangle(j).point1; triangle(j).point2];
plot(xy(:, 1), xy(:, 2), 'LineWidth', 2, 'Color', 'r');
hold off;

Answers (1)

Image Analyst
Image Analyst on 31 May 2023
Edited: Image Analyst on 31 May 2023
Try this:
% Demo by Image Analyst
clc; % Clear the command window.
close all; % Close all figures (except those of imtool.)
clear all;
workspace; % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 16;
% Get the name of the image the user wants to use.
baseFileName = 'images (3).jpeg';
folder = pwd;
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);
% Read in image.
rgbImage = imread(fullFileName);
% Get the dimensions of the image.
[rows, columns, numberOfColorChannels] = size(rgbImage)
% Display image.
subplot(2, 2, 1);
imshow(rgbImage, []);
axis on;
caption = sprintf('Original RGB Image\n%s', baseFileName);
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
% Set up figure properties:
% Enlarge figure to full screen.
g2 = gcf;
g2.WindowState = "maximized";
% Get rid of tool bar and pulldown menus that are along top of figure.
% set(gcf, 'Toolbar', 'none', 'Menu', 'none');
% Give a name to the title bar.
set(gcf, 'Name', 'Demo by ImageAnalyst', 'NumberTitle', 'Off')
% Segment the image.
[mask, maskedRGBImage] = createMask(rgbImage);
% Display image.
subplot(2, 2, 2);
imshow(mask, []);
axis on;
caption = sprintf('Color Segmentation Mask Image');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
% Clean mask.
% Fill black holes.
mask = imfill(mask, 'holes');
% Measure the areas so we can see how small is the smallest blob we want to consider.
props = regionprops(mask, 'Area');
allAreas = sort([props.Area])
% Take the blobs larger than 1000 pixels only
mask = bwareafilt(mask, [1000, inf]);
% Try to disconnect blobs that are tokuching by a little bit.
% Do an opening to break off any little tendrils
% diskRadius = 7;
% se = strel('disk', diskRadius, 0);
% mask = imopen(mask, se);
% Some tendrils may get disconnected. Take the large blobs only.
% mask = bwareafilt(mask, [1000, inf]);
% Do a closing to smooth out any little bays into the main objects.
% mask = imclose(mask, se);
% Fill black holes.
% mask = imfill(mask, 'holes');
% Display image.
subplot(2, 2, 3);
imshow(mask, []);
axis on;
caption = sprintf('Final Mask Image');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
% Get the circularity and area.
props = regionprops(mask, 'Circularity', 'Area');
circ = props.Circularity;
% Plot the borders of all the blobs in the overlay above the original grayscale image
% using the coordinates returned by bwboundaries().
% bwboundaries() returns a cell array, where each cell contains the row/column coordinates for an object in the image.
% Display image.
subplot(2, 2, 4);
imshow(rgbImage, []);
axis on;
caption = sprintf('Original RGB Image\n%s', baseFileName);
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
% Here is where we actually get the boundaries for each blob.
boundaries = bwboundaries(mask);
% boundaries is a cell array - one cell for each blob.
% In each cell is an N-by-2 list of coordinates in a (row, column) format. Note: NOT (x,y).
% Column 1 is rows, or y. Column 2 is columns, or x.
numberOfBoundaries = size(boundaries, 1); % Count the boundaries so we can use it in our for loop
% Here is where we actually plot the boundaries of each blob in the overlay.
hold on; % Don't let boundaries blow away the displayed image.
for k = 1 : numberOfBoundaries
thisBoundary = boundaries{k}; % Get boundary for this specific blob.
x = thisBoundary(:,2); % Column 2 is the columns, which is x.
y = thisBoundary(:,1); % Column 1 is the rows, which is y.
plot(x, y, 'r-', 'LineWidth', 2); % Plot boundary in red.
hold off;
caption = sprintf('%d Outlines, from bwboundaries()', numberOfBoundaries);
fontSize = 15;
title(caption, 'FontSize', fontSize);
axis('on', 'image'); % Make sure image is not artificially stretched because of screen's aspect ratio.
function [BW,maskedRGBImage] = createMask(RGB)
%createMask Threshold RGB image using auto-generated code from colorThresholder app.
% [BW,MASKEDRGBIMAGE] = createMask(RGB) thresholds image RGB using
% auto-generated code from the colorThresholder app. The colorspace and
% range for each channel of the colorspace were set within the app. The
% segmentation mask is returned in BW, and a composite of the mask and
% original RGB images is returned in maskedRGBImage.
% Auto-generated by colorThresholder app on 31-May-2023
% Convert RGB image to chosen color space
I = rgb2hsv(RGB);
% Define thresholds for channel 1 based on histogram settings
channel1Min = 0.542;
channel1Max = 0.788;
% Define thresholds for channel 2 based on histogram settings
channel2Min = 0.109;
channel2Max = 1.000;
% Define thresholds for channel 3 based on histogram settings
channel3Min = 0.517;
channel3Max = 1.000;
% Create mask based on chosen histogram thresholds
sliderBW = (I(:,:,1) >= channel1Min ) & (I(:,:,1) <= channel1Max) & ...
(I(:,:,2) >= channel2Min ) & (I(:,:,2) <= channel2Max) & ...
(I(:,:,3) >= channel3Min ) & (I(:,:,3) <= channel3Max);
BW = sliderBW;
% Initialize output masked image based on input image.
maskedRGBImage = RGB;
% Set background pixels where BW is false to zero.
maskedRGBImage(repmat(~BW,[1 1 3])) = 0;
Surabhi A S
Surabhi A S on 5 Jun 2023
Edited: Surabhi A S on 5 Jun 2023
Ok, let me tell you explain you what I need.
I have attached an image in which I have completed the triangles (edges) using red pen.
1. I need a code to join those (as marked) through MATLAB automatically.
2. After completing those triangles I have to calculate all three side lengths of each triangle and display the triangle and also its side length.

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