سلام
من سه تا Mfile از اینترنت گرفتم در مورد مامو گرافی
که در اول دو تا از mfiile ها از تابع function استفاده شده است.
و هر چی اجرا می کنم error می دهد
اگر می شود نحوه ی اجرای mfile هایی که دارای function هستند را به من بگویید.
مرسی از لطفتون....
*******************************
clear all
close all
function [im1]=SegmentMammo(im)
% [fname path]=uigetfile('*.pgm'
% im=imread(strcat(path,fname));
%figure,
%subplot(1,3,1),title('ACTUAL'
imshow(im);
[clusters, result_image, clusterized_image] = kmeansclustering(im, 3);
a=find(result_image<130);
b=find(result_image>200);
im1=im;
im1(a)=0;
im1(b)=0;
%subplot(1,3,3),imshow(im1),title('FINAL SEGMENTED IMAGE'
%subplot(1,3,2),imshow(result_image),title('S EGMENTATION PART'
end
end
**************************************
**************mammogreaphy-2******************
clear all
close all
function [clusters, result_image, clusterized_image] = kmeansclustering(im, k)
%histogram calculation
img_hist = zeros(256,1);
hist_value = zeros(256,1);
for i=1:256
img_hist(i)=sum(sum(im==(i-1)));
end;
for i=1:256
hist_value(i)=i-1;
end;
%cluster initialization
cluster = zeros(k,1);
cluster_count = zeros(k,1);
for i=1:k
cluster(i)=uint8(rand*255);
end;
old = zeros(k,1);
while (sum(sum(abs(old-cluster))) >k)
old = cluster;
closest_cluster = zeros(256,1);
min_distance = uint8(zeros(256,1));
min_distance = abs(hist_value-cluster(1));
%calculate the minimum distance to a cluster
for i=2:k
min_distance =min(min_distance, abs(hist_value-cluster(i)));
end;
%calculate the closest cluster
for i=1:k
closest_cluster(min_distance==(abs(hist_value-cluster(i)))) = i;
end;
%calculate the cluster count
for i=1:k
cluster_count(i) = sum(img_hist .*(closest_cluster==i));
end;
for i=1:k
if (cluster_count(i) == 0)
cluster(i) = uint8(rand*255);
else
cluster(i) = uint8(sum(img_hist(closest_cluster==i).*hist_value (closest_cluster==i))/cluster_count(i));
end;
end;
end;
imresult=uint8(zeros(size(im)));
for i=1:256
imresult(im==(i-1))=cluster(closest_cluster(i));
end;
clustersresult=uint8(zeros(size(im)));
for i=1:256
clustersresult(im==(i-1))=closest_cluster(i);
end;
clusters = cluster;
result_image = imresult;
clusterized_image = clustersresult;
end
****************************************
*****************
%% Read image
clear
f = im2double(imread('C:\Users\parto\Downloads\Fi g1006(a)(building).tif');
%% Display image
imshow(f,[]);title('Original image'
pause
%% Edge Detection
% [g, t] = edge(f, 'method', parameters);
%% Sobel Edge Detection
% automatic threshold
[v, t] = edge(f, 'sobel' , 'vertical'
imshow(v);title(sprintf('Sobel Edge Dectection [auto vertical t = %0.2f]',t));
pause
% manual threshold
t = 0.15;
v = edge(f, 'sobel', t, 'vertical'
imshow(v);title(sprintf('Sobel Edge Dectection [manual vertical t = %0.2f]',t));
pause
% Sobel edge +45 degree
w = [-2 -1 0; -1 0 1; 0 1 2];
v = imfilter(f, w, 'replicate'
t = 0.3*max(abs(v(
));
v = v >= t;
imshow(v);title(sprintf('Sobel Edge Dectection [manual +45 t = %0.2f]',t));
pause
% Sobel edge -45 degree
w = [0 1 2; -1 0 1; -2 -1 0];
v = imfilter(f, w, 'replicate'
t = 0.3*max(abs(v());
v = v >= t;
imshow(v);title(sprintf('Sobel Edge Dectection [manual -45 t = %0.2f]',t));
pause
%% Other methods
% Sobel
v0 = edge(f, 'sobel'
imshow(v0);title('Sobel Edge Dectection [auto]'
pause
% Prewitt
v1 = edge(f, 'prewitt'
imshow(v1);title('Prewitt Edge Dectection [auto]'
pause
% Roberts
v2 = edge(f, 'roberts'
imshow(v2);title('Roberts Edge Dectection [auto]'
pause
% Laplacian of Gaussian Method
v3 = edge(f, 'log'
imshow(v3);title('Laplacian of Gaussian Method [auto]'
pause
% Zero-cross
v4 = edge(f, 'zerocross'
imshow(v4);title('Zero-cross Method [auto]'
pause
% Canny
v5 = edge(f, 'canny'
imshow(v5);title('Canny Edge Dectection [auto]'
pause
subplot(231);imshow(v0);title('Sobel Edge Dectection [auto]'
subplot(232);imshow(v1);title('Prewitt Edge Dectection [auto]'
subplot(233);imshow(v2);title('Roberts Edge Dectection [auto]'
subplot(234);imshow(v3);title('Laplacian of Gaussian Method [auto]'
subplot(235);imshow(v4);title('Zero-cross Method [auto]'
subplot(236);imshow(v5);title('Canny Edge Dectection [auto]'
**************************************
من سه تا Mfile از اینترنت گرفتم در مورد مامو گرافی
که در اول دو تا از mfiile ها از تابع function استفاده شده است.
و هر چی اجرا می کنم error می دهد
اگر می شود نحوه ی اجرای mfile هایی که دارای function هستند را به من بگویید.
مرسی از لطفتون....
*******************************
clear all
close all
function [im1]=SegmentMammo(im)
% [fname path]=uigetfile('*.pgm'
% im=imread(strcat(path,fname));
%figure,
%subplot(1,3,1),title('ACTUAL'
imshow(im);
[clusters, result_image, clusterized_image] = kmeansclustering(im, 3);
a=find(result_image<130);
b=find(result_image>200);
im1=im;
im1(a)=0;
im1(b)=0;
%subplot(1,3,3),imshow(im1),title('FINAL SEGMENTED IMAGE'
;%subplot(1,3,2),imshow(result_image),title('S EGMENTATION PART'
end
end
**************************************
**************mammogreaphy-2******************
clear all
close all
function [clusters, result_image, clusterized_image] = kmeansclustering(im, k)
%histogram calculation
img_hist = zeros(256,1);
hist_value = zeros(256,1);
for i=1:256
img_hist(i)=sum(sum(im==(i-1)));
end;
for i=1:256
hist_value(i)=i-1;
end;
%cluster initialization
cluster = zeros(k,1);
cluster_count = zeros(k,1);
for i=1:k
cluster(i)=uint8(rand*255);
end;
old = zeros(k,1);
while (sum(sum(abs(old-cluster))) >k)
old = cluster;
closest_cluster = zeros(256,1);
min_distance = uint8(zeros(256,1));
min_distance = abs(hist_value-cluster(1));
%calculate the minimum distance to a cluster
for i=2:k
min_distance =min(min_distance, abs(hist_value-cluster(i)));
end;
%calculate the closest cluster
for i=1:k
closest_cluster(min_distance==(abs(hist_value-cluster(i)))) = i;
end;
%calculate the cluster count
for i=1:k
cluster_count(i) = sum(img_hist .*(closest_cluster==i));
end;
for i=1:k
if (cluster_count(i) == 0)
cluster(i) = uint8(rand*255);
else
cluster(i) = uint8(sum(img_hist(closest_cluster==i).*hist_value (closest_cluster==i))/cluster_count(i));
end;
end;
end;
imresult=uint8(zeros(size(im)));
for i=1:256
imresult(im==(i-1))=cluster(closest_cluster(i));
end;
clustersresult=uint8(zeros(size(im)));
for i=1:256
clustersresult(im==(i-1))=closest_cluster(i);
end;
clusters = cluster;
result_image = imresult;
clusterized_image = clustersresult;
end
****************************************
*****************
%% Read image
clear
f = im2double(imread('C:\Users\parto\Downloads\Fi g1006(a)(building).tif'
);%% Display image
imshow(f,[]);title('Original image'
;pause
%% Edge Detection
% [g, t] = edge(f, 'method', parameters);
%% Sobel Edge Detection
% automatic threshold
[v, t] = edge(f, 'sobel' , 'vertical'
;imshow(v);title(sprintf('Sobel Edge Dectection [auto vertical t = %0.2f]',t));
pause
% manual threshold
t = 0.15;
v = edge(f, 'sobel', t, 'vertical'
;imshow(v);title(sprintf('Sobel Edge Dectection [manual vertical t = %0.2f]',t));
pause
% Sobel edge +45 degree
w = [-2 -1 0; -1 0 1; 0 1 2];
v = imfilter(f, w, 'replicate'
;t = 0.3*max(abs(v(
));v = v >= t;
imshow(v);title(sprintf('Sobel Edge Dectection [manual +45 t = %0.2f]',t));
pause
% Sobel edge -45 degree
w = [0 1 2; -1 0 1; -2 -1 0];
v = imfilter(f, w, 'replicate'
;t = 0.3*max(abs(v(
));v = v >= t;
imshow(v);title(sprintf('Sobel Edge Dectection [manual -45 t = %0.2f]',t));
pause
%% Other methods
% Sobel
v0 = edge(f, 'sobel'
;imshow(v0);title('Sobel Edge Dectection [auto]'
;pause
% Prewitt
v1 = edge(f, 'prewitt'
;imshow(v1);title('Prewitt Edge Dectection [auto]'
;pause
% Roberts
v2 = edge(f, 'roberts'
;imshow(v2);title('Roberts Edge Dectection [auto]'
;pause
% Laplacian of Gaussian Method
v3 = edge(f, 'log'
;imshow(v3);title('Laplacian of Gaussian Method [auto]'
;pause
% Zero-cross
v4 = edge(f, 'zerocross'
;imshow(v4);title('Zero-cross Method [auto]'
;pause
% Canny
v5 = edge(f, 'canny'
;imshow(v5);title('Canny Edge Dectection [auto]'
;pause
subplot(231);imshow(v0);title('Sobel Edge Dectection [auto]'
;subplot(232);imshow(v1);title('Prewitt Edge Dectection [auto]'
;subplot(233);imshow(v2);title('Roberts Edge Dectection [auto]'
;subplot(234);imshow(v3);title('Laplacian of Gaussian Method [auto]'
;subplot(235);imshow(v4);title('Zero-cross Method [auto]'
;subplot(236);imshow(v5);title('Canny Edge Dectection [auto]'
;**************************************
دیدگاه