Fire Detection using Image Processing
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Hello!My project is stuck in at the point where my algorithm for detecting fire pixels detects areas that aren't fire.For some images it works perfectly but there are many things to improve.
What should I do to reduce areas that are not fire.I've been thinking removing regular areas but I think the fire pixel algorithm could be improved.What do you think?
Any help is welcomed.
The images resulted are 
and 
function densitate=calcDensitate(test,densitate,ksize)
r=(ksize-1)/2;
[linii,coloane]=size(densitate);
rowBound=linii-r;
colBound=coloane-r;
for j=r+1:colBound
col1=j-r;
col2=j+r;
delta=1;
for k=1:ksize
delta=delta+test(k,col2)-test(k,col1);
end
densitate(r,j)=densitate(r,j-1)+delta/255;
end
for i=r+1:rowBound
row1=i-r;
row2=i+r;
delta=1;
for k=1:ksize
delta=delta+test(row2,k)+test(row1,k);
end
densitate(i,r)=densitate(i-1,r)+delta/255;
end
for i=r+1:rowBound
for j=r+1:colBound
delta=(test(r+i,j+r)-test(i-r,j+r)-test(i+r,j-r)+test(i-r,j-r))/255;
densitate(i,j)=densitate(i-1,j)+densitate(i,j-1)-densitate(i-1,j-1)+delta;
end
end
This is the main function
img=imread('cadru230.jpg');
img=imgaussfilt(img,[3 3]);
tau=40;
subplot(2,2,1);
imshow(img);
red=img(:,:,1);
green=img(:,:,2);
blue=img(:,:,3);
%img=im2double(img);
hsv=rgb2hsv(img);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
ycbcrmap=rgb2ycbcr(img);
Y=ycbcrmap(:,:,1);
% Y=round(Y,2);
Cb=ycbcrmap(:,:,2);
% Cb=round(Cb,2);
Cr=ycbcrmap(:,:,3);
% Cr=round(Cr,2);
%%%%%%%%%%%%%calculare Ymean
[a,b]=size(Y);
SumaLinii=sum(Y);
total=sum(SumaLinii);
Ymean=total/(a*b);
[a,b]=size(Cb);
SumaLinii=sum(Cb);
total=sum(SumaLinii);
CbMean=total/(a*b);
% CbMean=round(CbMean,2);
%%%%%%%%%%%%%calculare CrMean
[a,b]=size(Cr);
SumaLinii=sum(Cr);
total=sum(SumaLinii);
CrMean=total/(a*b);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
h=hsv(:,:,1);
h=round(h,2);
s=hsv(:,:,2);
s=round(s,2);
v=hsv(:,:,3);
v=round(v,2);
[lin,col]=size(s);
test=ones(lin,col)*255;
for i=1:lin
for j=1:col
ss=1-3.0*min(red(i,j),min(green(i,j),red(i,j)))/(red(i,j) +green(i,j)+blue(i,j));
if(~(abs(Cb(i,j)-Cr(i,j)<tau)&&red(i,j)>180 && red(i,j)>=green(i,j) && green(i,j)>blue(i,j) && ss>=((255-red(i,j))*0.2/180) &&(v(i,j)>0.8 && v(i,j)<1)&& (Y(i,j)>=Ymean) && (Cb(i,j)<=CbMean) && (Cr(i,j)>=CrMean)))
%if(~(red(i,j)>=green(i,j) && green(i,j)>blue(i,j) && (red(i,j)>115 &&red(i,j)<135) && s(i,j)>(255-(red(i,j)*60)/120)))
test(i,j)=0;
%contor=contor+1;
end
end
end
BW2 = bwareaopen(test,100);
test=imclearborder(test);
stats = struct2table(regionprops(test,{'Area','Solidity','PixelIdxList'}));
idx = stats.Solidity < 0.9 | stats.Area <350;
for kk = find(idx)'
test(stats.PixelIdxList{kk}) = true;
end
subplot(2,2,2);
imshow(test);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%aplic denoise
r=(7-1)/2;
densitate=zeros(lin,col);
densitate=calcDensitate(test,densitate,7);
for i=r:lin-r
for j=r:col-r
count=densitate(i,j);
if(count<5)
test(i,j)=0;
end
end
end
subplot(2,2,3);
imshow(test);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%fill
test=medfilt2(test);
sv=fspecial('sobel');
sx=sv';
Gy=imfilter(test,sv,'replicate');
Gx=imfilter(test,sx,'replicate');
TL=0.39; %prag mic si prag mare
TH=0.98;
% kk=edge(test,'sobel',0.39);
% ll=edge(test,'sobel',0.98);
kk=edge(test,'sobel',0.39);
ll=edge(test,'sobel',0.98);
lll=edge(test,'canny',[TL TH]);
final=imadd(kk,ll);
edgePixels=nnz(final);
area=bwarea(final);
subplot(2,2,4);
imshow(final);
4 个评论
Shubham Channe
2020-4-18
Sir I'm Also trying same project and met with same issue if u got the coorect code can u please help me with correct code.
KALYAN ACHARJYA
2020-4-18
Because here you are manually adjusting the thresholding values based on specific single image
G Gion
2021-7-23
When we run this programme we are getting The error as not enough arguments
Walter Roberson
2021-7-23
You have to run the code that is labeled "This is the main function".
回答（2 个）
Alex Che
2020-4-21
1 个投票
That's the solution i found 8 months ago.I used the fluctuation of area and perimeter for every fire-like object and I put it into an algorithm to figure out which is fire. I also put a graphic which show the variation of area and number of pixels and for almost every video input works. In the frame 150 you observe a great variation of area for an object which represent the spreading fire.
Image Analyst
2020-4-18
0 个投票
Since there will be lamps and other things that could also be bright in the scene I think you'll have to analyze a video stream and see if the area of the bright things varies over time. See attached demo and adapt it as needed.
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2021-7-23
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