MATLAB: Hough parabola and represent it on image

image processingImage Processing Toolbox

Hi, I did not find anything about using hough to detect parabola in image to using maximum value accumulator. Can anyone help me or guide me. I really need it. Regards,

Best Answer

A paper on it: http://web.eecs.utk.edu/~qi/ece472-572/reference/htparabola-jafri.PDF

The FAQ on the paper: http://matlab.wikia.com/wiki/FAQ#Can_you_program_up_the_algorithm_in_this_article_for_me_and_explain_it_to_me.3F

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MATLAB: Peridiograma y Filtro media movil

Hola Pablo, creo poder ayudarte........

El periodograma se define como el modulo al cuadrado de la FFT dividivo por el total de datos.

Puedes Usar esta secuencia ------------------------------------------------------------------

ft  = fft(xt,padding);
amp = abs(ft).^2/(padding);

En el cado de filtro media movil, nos es algo muy complejo, de hecho tu mismo puedes diseñar el codigo.....

este es mi codigo

%function F=media_movil(X,p)

%function F=media_movil(X,p)
%filtro media movil centrada para datos
%(suavizacion)
%INPUT  X: serie de tiempo a suavizar
%       p: pesos del filtro
%claudioiturraulloa@gmail.com Claudio Iturra
X=nm(:,4);   Una columna cualquiera de datos, en este caso, es la cuarta columna
%p=[1/3 1/3 1/3];
p=([1:25]*0+1)';
p=p/(sum(p));
P=X+NaN;
N=length(X);
np=length(p);
np2=fix(np/2);
for i=np2+1:N-(np2+1)
    P(i)=X(i-np2:i+np2)'*p;
end
plot([X P])

espero que te sirva, para obtener respuestas con mayor rapidez trata de escribirlas en Ingles, adios

MATLAB: Matrix dimensions must agree.

This works

% n all alpha beta gamma min max
d=[1	550	8.1000	0.00028	0	680
   2	309	8.1000	0.00056	0	360
   3	307	8.1000	0.00056	0	360
   4	240	7.7400	0.00324	60	180
   5	240	7.7400	0.00324	60	180
   6	240	7.7400	0.00324	60	180
   7	240	7.7400	0.00324	60	180
   8	240	7.7400	0.00324	60	180
   9	240	7.7400	0.00324	60	180
   10	126	8.6000	0.00284	40	120
   11	126	8.6000	0.00284	40	120
   12	126	8.6000	0.00284	55	120
   13	126	8.6000	0.00284	55	120];
Pd=1800; %Pdemand 
alpha=d(:,2);   %%%%%%%%%%%%%%
n=d(:,1);
beta=d(:,3);
gamma=d(:,4);
Pmin=d(:,5);
Pmax=d(:,6); 
DelP=Pd; i=1;
Iteration=i;
Lamda=8.35; % assume lambda L(i,1)=Lamda;
while abs(DelP)> 0.00001 
P=(Lamda-beta)./(gamma.*2);
P=min(P,Pmax);	%p=ph if pmax<p//p>pmax	//pick pmax bila pmax kecil dri p
P=max(P,Pmin);	%p=pl if pmin>p//p<pmin
DelP=Pd-sum(P); Lamda=Lamda+DelP/(sum(1./(2*gamma)));
costI(:,i)=alpha+(beta.*P)+(gamma.*P.*P); 
totalCost_iteration(i,1)=sum(costI(:,i));
Iteration(i,1)=i;
% Lamda(i,1)=Lamda;  % This causes a problem during the iterations
i=i+1;
end
Cost=alpha+(beta.*P)+(gamma.*P.*P); % Costs
totalCost=sum(Cost);  %%%%%%%%%%%%%%%%%%%
totalPower=sum(P); table(d(:,1),P,Cost,'V',{'Unit' 'Power' 'Cost'})
display(totalCost); 
display(totalPower);
figure
plot(Iteration,totalCost_iteration)
title('Convergest Graph') 
xlabel('Number of Iteration') 
ylabel('Cost(RM/h)')

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MATLAB: Peridiograma y Filtro media movil

MATLAB: Matrix dimensions must agree.

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