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Sobel edge detection

         The gradient of the image is calculated for each pixel position in the image.






























The procedure and the MATLAB  code for sobel edge detection without using MATLAB built-in function:


































MATLAB CODE:


A=imread('peppers.png');
B=rgb2gray(A);

C=double(B);


for i=1:size(C,1)-2
    for j=1:size(C,2)-2
        %Sobel mask for x-direction:
        Gx=((2*C(i+2,j+1)+C(i+2,j)+C(i+2,j+2))-(2*C(i,j+1)+C(i,j)+C(i,j+2)));
        %Sobel mask for y-direction:
        Gy=((2*C(i+1,j+2)+C(i,j+2)+C(i+2,j+2))-(2*C(i+1,j)+C(i,j)+C(i+2,j)));
     
        %The gradient of the image
        %B(i,j)=abs(Gx)+abs(Gy);
        B(i,j)=sqrt(Gx.^2+Gy.^2);
     
    end
end
figure,imshow(B); title('Sobel gradient');
Sobel Gradient

%Define a threshold value
Thresh=100;
B=max(B,Thresh);
B(B==round(Thresh))=0;

B=uint8(B);
figure,imshow(~B);title('Edge detected Image');












Edge detected Image



Edge detected Image(Threshold value:35)
The edge detected image can be obtained from the sobel gradient by
using a threshold value.


  • If the sobel gradient values are lesser than the threshold value then replace it with the threshold value.
    if f < threshold value then
    f = threshold value.

























To avoid complex computation, the gradient can also be computed using the formula:




The Image obtained from computing X-direction derivative:













The Image obtained from computing Y-direction derivative:

Also Check  Sobel Edge Detection - Part 2







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Darker Edges


Captured Image

Last week my friend was in need of her signature in digital format. Fortunately, it was not for any official purpose. So we captured the signature using the camera and used it.

The image that we acquired using the camera was not that much good. So we processed the image and then included in the document.

After this thing happened, I thought of trying the image with MATLAB.
First I adjusted the image intensity using the imadjust function . 
The syntax for the imadjust for rgb image is
imadjust(RGB,[Low_R Low_G Low_B; High_R High G High B],[]);
The Low values should always be lower than High values.
The range of these values between 0 to 1.
After Imadjust

Then I detected the edge of the image. Then to enlarge the image parts I dilated it. Use an appropriate structure element. Here I used 'disk'.
After that, using labeling method, I labeled all the connected components. Based on the size of the components the components where finally used and components whose size are less are ignored.
Edge detected Image

MATLAB CODE:



function my_edge
global filename A I ;
scz=get(0,'ScreenSize');
figure('Position',[round(scz(1,3)/4) round(scz(1,4)/8) 700 500],'MenuBar','None','NumberTitle','off','Name','Pencil sketch Application','Resize','off');
axes('Position',[0 0 .7 1],'xtick',[],'ytick',[]);
Low=uicontrol('Style','slider','Position',[500,280 200 20],'Max',0.99 ,'Min',0,'Value',0.0,'SliderStep',[0.05,0.1],'Callback',@draw);
High=uicontrol('Style','slider','Position',[500,370 200 20],'Max',1,'Min',0.1,'Value',.5,'SliderStep',[0.05,0.1],'Callback',@draw);
uicontrol('Style','pushbutton','String','Done','Position',[500 200 40 20],'Callback',@pushme);
directory=dir('*.jpg');
files={directory.name}';
uicontrol('style','text','Position',[500,310 100 20]','String','Low:');
uicontrol('style','text','Position',[500,395 100 20]','String','High :');
uicontrol('style','text','Position',[500,455 100 20]','String','Filename:');
uicontrol('Style','popupmenu','position',[500 420 160 30],'Value',1,'String',files,'Callback',@displayfile);
    function displayfile(obj,eve)
        ptr=get(obj,'value');
        filename=char(files(ptr));
        A=imread(filename);
        A=imresize(A,0.4);
        subplot('Position',[0.05 0.1 .6 .9]);imshow(A);
    end
    function draw(obj,eve)
        H=get(High,'Value');
        L=get(Low,'Value');
      uicontrol('Style','edit','position',[500 250 50 20],'String',L);
      uicontrol('Style','edit','position',[500 340 50 20],'String',H);
        if( L < H )
            %The intensity values for each R,G,B planes are adjusted.
            I=imadjust(A,[L L L; H H H],[]);
        end
           subplot('Position',[0.05 0.1 .6 .9]);imshow(I);
       end
                                                                                                         
                                                                                        
                                                                                         
                                                                                   
                                                                                    
    function pushme(obj,eve)
        myedges(I);
    end
    function myedges(A)
      
A1=rgb2gray(A);
B=(edge(A(:,:,1))|edge(A(:,:,2))|edge(A(:,:,3)));

Edge detected




SE=strel('disk',3);
C=~(imdilate(B,SE));
target=(ones([size(A1,1) size(A1,2)] ));
[BW,label]=bwlabel(~C,8);
for l=1:max(max(label))
[row, col] = find(BW==l);
if(size(row,1)>30)
for i=1:size(row,1)
    x=row(i,1);
    y=col(i,1);
    target(x,y)=C(x,y);
end
end
end


subplot('Position',[0 0.5 .8 .45]);imshow(A);title('Original Image');
subplot('Position',[0 0   .8 .45]);imshow(target);title('Final Image');
    end
end


Another example:

After Imadjust and edge detection (structuring element:disk Radius=1)


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Image Shading in MATLAB

         
              Here I tried to shade the RGB image which results in a pencil sketched type image. The user selects the image from the pop-up menu and by adjusting the line value in the slider, the edge thickness is made.
By adjusting the thresh value in the slider the image shade is increased or decreased.
Additional Information:
To make your own pencil sketch without using MATLAB try Autodesk Sketchbook.
Based on the customers review, this software is best to try on low pixel camera images.
Steps To Be Performed:

1.     Input a RGB image
2.     Convert the image to grayscale image.
3.     Find the edges using Sobel Method.[gradient Estimation]
4.     Filter the Image to obtain the image without noise
4.1.          The blurred or unsharp image is subtracted from the image to obtain the sharpened image.
5. Blend the edge and the sharpened image.



MATLAB Code:

function image_shade

The GUI is designed.

global filename A;
scz=get(0,'ScreenSize');
figure('Position',[round(scz(1,3)/4) round(scz(1,4)/8) 700 500],'MenuBar','None','NumberTitle','off','Name','Pencil sketch Application','Resize','off');
axes('Position',[0 0 .7 1],'xtick',[],'ytick',[]);
shade=uicontrol('Style','slider','Position',[500,310 200 20],'Max',1 ,'Min',0.01,'Value',0.56,'Callback',@draw);
thresh=uicontrol('Style','slider','Position',[500,370 200 20],'Max',255,'Min',0,'Value',30,'Callback',@draw);
directory=dir('*.jpg');
files={directory.name}';
tval=uicontrol('style','text','Position',[500,340 100 20]','String','Thresh :');
line=uicontrol('style','text','Position',[500,395 100 20]','String','Line :');
uicontrol('style','text','Position',[500,455 100 20]','String','Filename:');
uicontrol('Style','popupmenu','position',[500 420 160 30],'Value',1,'String',files,'Callback',@displayfile);

    function displayfile(obj,~)
        ptr=get(obj,'value');
        filename=char(files(ptr));
        A=imread(filename);                      
        imshow(A);
    end
    function draw(~,~)
       
        sh=get(shade,'Value');
        thr=get(thresh,'Value');
        thval=strcat('Thresh :', num2str(sh));
        set(tval,'String',thval);
       
        lineval=strcat('Line :', num2str(thr));
        set(line,'String',lineval);
       if(~isempty(A))
        A=imread(filename);
        B=rgb2gray(A);


The Edge of the image is detected using the sobel edge detection method.


C3=~edge(B,'sobel','VERTICAL');
C2=~edge(B,'sobel','HORIZONTAL');
C=uint8(C3.*C2);

The image is sharpened by subtracting the blur image.

F1=uint8(imfilter(B,fspecial('unsharp')/sh));

The blending of the edge and the filtered image is done.

for m=1:size(F1,1)
    for n=1:size(F1,2)
        if(C(m,n)==0)
           F1(m,n)=B(m,n)-thr;
        end
    end
end


imshow(F1);
       end
    end
end






Shaded Image

Original Image




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