Geek Answers Handbook

Kant edge detector in MATLAB

I am trying to execute a canny edge detector without calling the canny function in Matlab. I wrote several functions for a Gaussian filter (sigma = 1) and non-aggressive suppression. The original image and the resulting image are displayed. Not sure error ...

Source image

enter image description here

Output i get

enter image description here

I attached the code:

%% Read in I = imread('fruit.jpg'); figure(1),imshow(I) I = double(I); %% Determine Mask Size sigma = 2; w = mask_size(sigma); %% Gaussian Smoothing Filter [ G,sum ] = gauss_mask(w,sigma); %% Convolve I1 = (1/sum) * image_convolution(I,w,G); figure(2),imshow(I1); %% Ix(derivative in x-direction) Ix= delx(I1); figure(3),imshow(Ix); %% Iy(derivative in y-direction) Iy= dely(I1); figure(4),imshow(Iy); %% Gradient Magnitude If = grad_mag(Ix,Iy); figure(5),imshow(If); %% Non-maxmimum suppression It = suppression(If,abs(Ix),abs(Iy)); figure(6),imshow(It); function [ G,sum ] = gauss_mask( w,sigma ) min = 1; m = floor(w/2); sum = 0; for x = 1: w for y = 1:w g = xm-1; h = ym-1; k = -(g^2 +h^2)/(2*sigma^2); G(x,y) = exp(k); sum = sum + G(x,y); if min > G(x,y) min = G(x,y); end end end B=1/min; G= B * G; G = round(G); end function [ I2 ] = image_convolution(I,w,G) m= (w-1)/2; N= size(I,1); M=size(I,2); for i=1:N for j=1:M if (i > Nm-1 || j > Mm-1 || i<m+1 || j <m+1) I2(i,j) = 0; continue; end sum1 = 0; for u=1:w for v=1:w sum1 = sum1+I(i+um-1,j+vm-1)*G(u,v); end end I2(i,j)=sum1; end end end function [ Ix ] = delx( image ) mask = [-1 0 1; -2 0 2; -1 0 1]; Ix =image_convolution(image,3,mask); end function [ Iy ] = dely( image ) mask = [-1 -2 -1;0 0 0;1 2 1]; Iy =image_convolution(image,3,mask); end function [ Imag ] = grad_mag(Ix,Iy) m=size(Ix,1); n=size(Ix,2); for i=1:m for j=1:n Imag(i,j) =sqrt(Ix(i,j)^2 + Iy(i,j)^2); end end end function [ It ] = suppression( If,Ix,Iy ) m=size(Ix,1); n=size(Ix,2); for i = 1:m for j=1:n if (j == 1 || j == n || i == 1 || j == n) It(i,j) = 0; else if (Ix(i,j)*Iy(i,j)> 0) f1 =If(i-1,j-1); f2 =If(i,j); f3 =If(i+1,j+1); It(i,j) = thinning(f1,f2,f3); else if(Ix(i,j)*Iy(i,j)< 0) f1 =If(i+1,j-1); f2 =If(i,j); f3 =If(i-1,j+1); It(i,j) = thinning(f1,f2,f3); else if(abs(Ix(i,j))-abs(Iy(i,j))>5) f1 =If(i-1,j); f2 =If(i,j); f3 =If(i+1,j); It(i,j) = thinning(f1,f2,f3); else if(abs(Iy(i,j))-abs(Ix(i,j)) > 5) f1 =If(i,j-1); f2 =If(i,j); f3 =If(i,j+1); It(i,j) = thinning(f1,f2,f3); end end end end end end end end function [ w ] = thinning( f1,f2,f3 ) if( f2>f1 && f2>f3) w =1; else w= 0; end end function sz = mask_size(sigma) sz = floor(6*sigma) + 1; end

There is a lot of noise ... how can I solve this error? I need help...

+7
source share
4 answers

The error is actually in the thinning function.

  if( f2>f1 && f2>f3) w =f2; else w= 0;
+4
source

You should do both:

Take more T1 when you execute this part of the algorithm:

 Define two thresholds T1 > T2 for every pixel with value greater than T1 is presumed to be an edge pixel.
+3
source

Your problem is the threshold adding a strong thresholder to get rid of the false edges.

First you need to smooth the image using the Gauss function. Then find the gradient and magnitude of the input image. Perform Nemaxim Suppression. After that, the threshold hysteresis values ​​are performed.

0
source

When I see your image on the output, I can say that you should check ..

  • The hysteresis function is working normally or not.
  • You can make the HIGH threshold a little higher
  • You can smooth the image a bit.
0
source

More articles:


All Articles