%############################################
%###### Preprocessing of the lane image #####
%############################################
% I=imread('Image.jpg'); % Read image from database
% I=rgb2gray(I); % Convert a color image to gray image
I=imresize(I,[100,500]); % Changing the image size to 100*500 pixels
%>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
L_vpp=sum(I,1);
L_vpp=500*(L_vpp-min(L_vpp))/(max(L_vpp)-min(L_vpp));
P=5; % P Equal to half of Averaged Range - width of Lane is 40 pixels
L_vpp1=L_vpp;
% S_vpp is signal that removed noise
for i=P+1:size(L_vpp,2)-P
    L_vpp(i)=sum(L_vpp1(i-P:i+P))/9;
end
% plot(L_vpp1,'r','LineWidth',2)
% hold on
% plot(L_vpp,'b','LineWidth',2)
%>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
PLans={};
SlopeThreshold=0.000001;
AmpThreshold=0;
smoothwidth=2;
peakgroup=5;
smoothtype=5;
P=peakfind([1:size(L_vpp,2)],L_vpp,SlopeThreshold,AmpThreshold,smoothwidth,peakgroup,smoothtype);
% subplot(2,1,1)
% imshow(I);
% subplot(2,1,2)       
% plot([1:size(L_vpp,2)],L_vpp);hold on;plot(P(:,2),P(:,3),'*g')