Has anyone implemented moravec corner detector in matlab??
2 Ansichten (letzte 30 Tage)
Ältere Kommentare anzeigen
B.k Sumedha
am 20 Mai 2015
Beantwortet: Ignacio Rocco
am 14 Nov. 2019
This is what i have tried.But with very less accurate.
clear all
close all
clc
tic
I=imread('panorama_image1.jpg');
originalmap=I;
w=5;
m=floor(size(I,1)/w);
n=floor(size(I,2)/w);
c=ceil(w/2)+(0:n-1)*w;
r=ceil(w/2)+(0:m-1)*w;
step=floor(w/2);
for y_unit=1:m
for x_unit=1:n
v1=0;v2=0;v3=0;v4=0;
for i=-step:step-1
v1=v1+(I(r(y_unit),c(x_unit)+i)-I(r(y_unit),c(x_unit)+i+1))^2;
v2=v2+(I(r(y_unit)+i,c(x_unit)+i)-I(r(y_unit)+i+1,c(x_unit)+i+1))^2;
v3=v3+(I(r(y_unit)+i,c(x_unit))-I(r(y_unit)+i+1,c(x_unit)))^2;
v4=v4+(I(r(y_unit)-i,c(x_unit)+i)-I(r(y_unit)-i-1,c(x_unit)+i+1))^2;
end
IV_cr(y_unit,x_unit)=min([v1,v2,v3,v4]);
end
end
exper_thr=20;
IV_cr(IV_cr<exper_thr)=NaN;
wf=9;
mf=floor(m/wf);
nf=floor(n/wf);
xc=[];
yc=[]; for y_unit=1:mf
for x_unit=1:nf
[C,I]=max(IV_cr((y_unit-1)*wf+1:y_unit*wf,(x_unit-1)*wf+1:x_unit*wf))
[C1,I1]=max(C);
IV_crch(y_unit,x_unit)=C1;
row=I(I1);
col=I1;
crch_row(y_unit,x_unit)=(y_unit-1)*wf+row;
crch_col(y_unit,x_unit)=(x_unit-1)*wf+col;
yc=[yc,r((y_unit-1)*wf+row)];xc=[xc,c((x_unit-1)*wf+col)];
IV_cr((y_unit-1)*wf+1:y_unit*wf,(x_unit-1)*wf+1:x_unit*wf)=NaN;
IV_cr((y_unit-1)*wf+row,(x_unit-1)*wf+col)=C1;
end
end
figure(1)
imshow(originalmap)
figure(2)
plot(xc,yc,'*')
view(0,-90)
toc;
t=toc;
disp(['amount of time',num2str(t),'sec'])
figure(3)
imshow(originalmap)
hold on
plot(xc,yc,'R*')
axis on
end
0 Kommentare
Akzeptierte Antwort
Thorsten
am 20 Mai 2015
I just did if for you:
function C = moravec(I)
%MORAVEC Moravec corner detector
%
% C = MORAVEC(I)
%
% Thorsten.Hansen@psychol.uni-giessen.de 2015-05-20
if nargin == 0 % simple test
I = zeros(100);
I(40:60, 40:60) = 1;
C = moravec(I);
imshow(0.5*C+I, [])
if nargout == 0, clear C, end
return
end
D(:,:,1) = diff([I I(:,end)]')';
D(:,:,2) = diff([I(:,1) I]')';
D(:,:,3) = diff([I; I(end,:)]);
D(:,:,4) = diff([I(1,:); I]);
C = sum(D.^2, 3);
if nargout == 0, clear C, end
12 Kommentare
Thorsten
am 20 Mai 2015
Bearbeitet: Thorsten
am 20 Mai 2015
What do you mean by "Bad luck"? Does the result look strange, or do you get a Matlab error? The Moravec detector is highly sensitive to noise, so you get fine results for artificial images (run moravec without arguments to see an overlay of the image and the detected corners), but less so for natural images.
Weitere Antworten (1)
Ignacio Rocco
am 14 Nov. 2019
Hi,
Thanks Thorsten for your code! However I think it's missing a few details. I slightly modified the implementation according to the original text by Moravec [1980], and I think now it's producing much better results.
Here's the updated code.
function C = moravec(I)
%MORAVEC Moravec corner detector
%
% C = MORAVEC(I)
%
% Thorsten.Hansen@psychol.uni-giessen.de 2015-05-20
% Ignacio.Rocco@inria.fr 2019-11-14
if nargin == 0 % simple test
I = zeros(100);
I(40:60, 40:60) = 1;
C = moravec(I);
imshow(0.5*C+I, [])
if nargout == 0, clear C, end
return
end
D(:,:,1) = conv2(conv2(single(I),[1 -1],'same').^2,ones(3),'same');
D(:,:,2) = conv2(conv2(single(I),[1;-1],'same').^2,ones(3),'same');
D(:,:,3) = conv2(conv2(single(I),[1 0;0 -1],'same').^2,ones(3),'same');
D(:,:,4) = conv2(conv2(single(I),[0 1;-1 0],'same').^2,ones(3),'same');
C = min(D.^2,[], 3);
if nargout == 0, clear C, end
0 Kommentare
Siehe auch
Kategorien
Mehr zu Feature Detection and Extraction finden Sie in Help Center und File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!