first commit

Author: Uniqcoda

.DS_Store

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+# edge-detection-image-processing

README.md

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+% funtion to draw my initials on my photo
+function my_im = draw_initials(im)
+    % Add my initials (letter M), with triple lines to make it obvious
+    for i=30:270
+        % left vertical line: set red and green to zero to make blue line
+        im(i,30,1:2)=0;
+        im(i,31,1:2)=0;
+        im(i,32,1:2)=0;
+        % right vertical line: set green to 255 to make green
+        im(i,270,2)=255;
+        im(i,269,2)=255;
+        im(i,268,2)=255;
+        if (i <= 150)  % 150 is the mid-point between 30 and 270
+            % left diagonal: set red to zero to make cyan
+            im(i,i,1)=0;
+            im(i+1,i,1)=0;
+            im(i+2,i,1)=0;
+            % right diagonal: set all rgb to zero make black 
+            im(i,270-i+30,1:3)=0;
+            im(i+1,270-i+30,1:3)=0; 
+            im(i+2,270-i+30,1:3)=0; 
+        end
+    end
+    my_im = im;
+end

draw_initials.m

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+function [gray_seg, gray_edge] = get_gray_edge(grayImg)     
+    [row, col, ~] = size(grayImg);
+    %{ 
+    row = 824, col = 922, dim = 1
+    when I checked the improfile of the grayscale, my face had values of
+    between 110 and 170 
+    %}
+    thresh1 = 110;
+    thresh2 = 170;
+
+    for i=1:row
+        for j=1:col
+            if (grayImg(i,j)>thresh1 && grayImg(i,j)<thresh2)
+                grayImg(i,j)=255; % for skin tone
+            else
+                grayImg(i,j)=0; % for background
+            end
+        end
+    end
+    se = strel('disk', 2);
+    erodedMask = imerode(grayImg, se);
+    gray_seg = imdilate(erodedMask, se);
+    gray_edge = edge(gray_seg,"roberts");
+end

get_gray_edge.m

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+% Edge detection using threshold of HSV color space
+function [hsv_edge, imFace] = get_hsv_edge(im, hsvImg)
+    % copy the image, to preserve the original
+    im1 = hsvImg;
+    [row, col, ~] = size(im1);
+    imFace = zeros(row,col);
+    %{ 
+    row = 824, col = 922, dim = 3
+    when I checked the improfile of the picture, my face had
+    1. h value btw 0.02 and 0.07, while the background had h value above
+    0.5 
+    2. s value of btw 0.28 and 0.42 while the background had s value below
+    0.2 
+    3. v value of btw 0.5 and 0.7 while the background was either above or
+    below that range.
+    %}
+
+    hueThreshold = 0.08;
+    saturationThreshold = 0.2;
+
+    for i=1:row
+        for j=1:col
+            if (im1(i,j,1)<hueThreshold && im1(i,j,2)>saturationThreshold)
+                % 1 for my face and 0 for the background
+                imFace(i,j) = im(i,j,1);
+            end
+        end
+    end
+    hsv_edge = edge(imFace,"roberts");
+end

get_hsv_edge.m

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+function [edges, overlay] = get_kmeans_edge(hsvImg)
+    img = uint8(hsvImg);
+    % Perform k-means segmentation on the HSV image
+    k = 6; % Number of clusters
+    [L, ~] = imsegkmeans(img, k);
+
+    % Extract the binary mask for the first cluster
+    mask = (L==1);
+
+    % Covert label to RGB image to visualize the binary mask
+    maskRgb = label2rgb(mask);
+
+    % Overlay the mask on top of the rgb image
+    overlay = labeloverlay(maskRgb, mask);
+
+    edges = edge(rgb2gray(overlay), 'roberts');
+end

get_kmeans_edge.m

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+function myCW3()
+    im = imread("photo1.jpg");
+
+    [~, ~, dim] = size(im);
+    if dim > 1
+        % convert to gray image, if the image is not gray
+        grayImg1 = rgb2gray(im);
+    else
+        grayImg1 = im;
+    end
+
+    % 1. draw my initials
+    my_im = draw_initials(im);
+
+    % 2. Matlab inbuilt method
+    edge_rob = edge(grayImg1, "roberts");
+
+    % 3. Using convolution mask
+    myedge = my_edge(grayImg1);
+
+    % convert to hsv
+    hsvImg = rgb2hsv(im);
+
+    % 4. Edge detection using HSV and thresholds
+    [hsv_edge, hvs_seg] = get_hsv_edge(im, hsvImg);
+
+    % 5. Edge detection using Gray image and thresholds
+    [gray_seg, gray_edge] = get_gray_edge(grayImg1);
+    
+    % 6. Edge detection using k-means
+    [edgeKM, overlay] = get_kmeans_edge(hsvImg);
+
+    % 7. Edge detection using SVM
+    svm_edge = get_svm_edge(im);
+
+    % Larger image with my initials
+    figure(2), imshow(my_im), title("Original with initials");
+    
+    % Subplots of all results
+    figure(1),
+    subplot(3,4,1), imshow(im);
+    title("1. Original")
+    subplot(3,4,2), imshow(edge_rob);
+    title("2. Default Roberts")
+    subplot(3,4,3), imshow(myedge);
+    title("3. My Conv Edge")
+    subplot(3,4,4), imshow(hvs_seg);
+    title("4. HSV Segment")
+    subplot(3,4,5), imshow(hsv_edge);
+    title("5. HSV Edge: Roberts")
+    subplot(3,4,6), imshow(edge(hvs_seg,"sobel"));
+    title("6. HSV Edge: Sobel")
+    subplot(3,4,7), imshow(gray_seg);
+    title("7. Gray Segment")
+    subplot(3,4,8), imshow(gray_edge);
+    title("8. Gray Edge: Roberts")
+    subplot(3,4,9), imshow(edge(gray_seg,"sobel"));
+    title("9. Gray Edge: Sobel")
+    subplot(3,4,10), imshow(overlay);
+    title("10. K-Means Overlay")
+    subplot(3,4,11), imshow(edgeKM);
+    title("11. K-Means Edge")
+    subplot(3,4,12), imshow(svm_edge);
+    title("12. SVM Edge")
+end

myCW3.m

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+function myedge = my_edge(im)
+    % Using convolution mask
+    h = [
+        1, 0, 1;
+        0, 1, 0;
+        -1, -1, -1;
+    ];
+    % my work
+    myedge = conv2(im, h);