www.pudn.com > MatlabSIFT.zip > test.m

 
%example file for feature detector 
 
%close all 
 
testpat=0; %set to zero to use current contents of img variable 
 
if testpat==1 
     
    img=zeros(400,400); 
    img(150:200,100:150)=200; 
    img(100:110,100:110)=200; 
    img(100:118,140:158)=200; 
    img(100:120,185:205)=200; 
    img(100:125,235:260)=200; 
    img(100:130,290:320)=200; 
    img(150:185,40:75)=200; 
    img(190:290,190:290)=200; 
    img(300:302,100:102)=200; 
         
    img=filter_gaussian(img,7,sqrt(2)); 
    img=img+randn(400,400)*5; 
     
elseif testpat==2 
     
    img=zeros(400,400); 
    img(200:400,190:210) = 200; 
    img=filter_gaussian(img,7,sqrt(2)); 
    img=img+randn(400,400)*5; 
     
elseif testpat==3 
     
    img=zeros(400,400); 
    img(1:400,190:210) = 200; 
    img=filter_gaussian(img,7,sqrt(2)); 
    img=img+randn(400,400)*5; 
     
elseif testpat==4 
     
    img=zeros(400,400); 
    img(200:400,190:210) = 200; 
    img(200:220,200:400) = 200; 
    img=filter_gaussian(img,7,sqrt(2)); 
    img=img+randn(400,400)*0; 
     
elseif testpat==5 
     
    img=zeros(400,400); 
    img(200:400,200:210) = 200; 
    img(200:210,1:400) = 200; 
    img=filter_gaussian(img,7,sqrt(2)); 
    img=img+randn(400,400)*5; 
     
elseif testpat==6 
     
    img=zeros(400,400); 
    img(1:400,200:210) = 200; 
    img(200:210,1:400) = 200; 
    img=filter_gaussian(img,7,sqrt(2)); 
    img=img+randn(400,400)*5; 
    img=-img; 
 
end     
 
close all 
 
if size(img,3)>1  
    img = rgb2gray(img); 
end 
 
%imagesc(img); 
 
threshold=3;        %Threshold value for rejecting maxima/minima 
disp_flag = 0;      %change to a zero for a combined view of all scales 
img_flag = 1;       %change to a zero to see features plotted on original image 
radius = 4; 
radius2 = 4; 
radius3 = 4; 
min_sep = .04; 
edgeratio = 5; 
scl = 1.5; 
 
%img = imread(file_name); 
%[pyr,imp] = build_pyramid(img,12,scl); 
 
%pts = find_features(pyr,img,scl, threshold,radius,radius2,min_sep,edgeratio,disp_flag,img_flag); 
 
%[features] = getpts(img,pyr,scl,imp,pts,6,radius3,min_sep,edgeratio); 
 
[features,pyr,imp,keys] = detect_features(img,scl,disp_flag,threshold,radius,radius2,radius3, min_sep,edgeratio); 
 
showfeatures(features,img); 
axis equal; 
 
%enjoy...