my matlab code:
% Initialization steps.
clc;
clearvars;
close all;
workspace;
fontSize = 16;
objects = imaqfind; %find video input objects in memory % מחפש את כל קלטי הוידאו שבזכרון
delete(objects) %delete a video input object from memory %מאפס את כל קלטי הוידאו
load('cameraParams1.mat')% נתונים מהקליברציה
focalLength = [cameraParams.FocalLength(1), cameraParams.FocalLength(2)]; % [fx, fy] in pixel units
principalPoint = [cameraParams.PrincipalPoint(1), cameraParams.PrincipalPoint(2)]; % [cx, cy] optical center in pixel coordinates
imageSize = cameraParams.ImageSize; % [nrows, mcols] 480x640
camIntrinsics = cameraIntrinsics(focalLength, principalPoint, imageSize); %מאחסן את הפרמטרים של המצלמה
height = 0.15; % mounting height in meters from the ground -גובה מיקום המצלמה
pitch = 30; % pitch of the camera in degrees -זווית המצלמה
yaw = 0; % yaw of the camera in degrees
roll = 0; % roll of the camera in degrees
sensor = monoCamera(camIntrinsics, height, 'Pitch', pitch,'Yaw',yaw,'Roll',roll); % חיישן המצלמה- גובה וזווית המצלמה
videoName = 'test3.mp4';
videoReader = VideoReader(videoName);
timeStamp = 0.06667; % time from the beginning of the video
videoReader.CurrentTime = timeStamp; % point to the chosen frame
frame = readFrame(videoReader); % read frame at timeStamp seconds
imshow(frame) % display frame
% Using vehicle coordinates, define area to transform
distAheadOfSensor = 1.; % in meters, as previously specified in monoCamera height input-
spaceToOneSide = 0.5; % all other distance quantities are also in meters-
bottomOffset = 0.15;
outView = [bottomOffset, distAheadOfSensor, -spaceToOneSide, spaceToOneSide]; % [xmin, xmax, ymin, ymax]
imageSize = [NaN, 1000]; % output image width in pixels; height is chosen automatically to preserve units per pixel ratio
birdsEyeConfig = birdsEyeView(sensor, outView, imageSize);
% birdsEyeImage = transformImage(birdsEyeConfig, frame);
% figure
% imshow(birdsEyeImage)
% % העברה מצבעוני לאפור
frame = rgb2gray(frame);
figure
imshow(frame)
% העברה לבינארי
frame(frame<170)=0;
figure
imshow(frame)
if ndims(frame) == 3
% It's color. Take the red channel.
grayImage = frame(:, :, 1);
end
figure
imshow(frame, []);
impixelinfo;
axis('on', 'image')
mask = logical(frame > 140 & frame < 255);
mask = bwareafilt(mask, 2); % Make sure we have only two lines.
mask = bwskel(mask);
figure
imshow(mask);
impixelinfo;
axis('on', 'image')
labeledImage = bwlabel(mask);
line1 = ismember(labeledImage, 1);
line2 = ismember(labeledImage, 2);
% Get rows and columns of each line.
[r1, c1] = find(line1);
[r2, c2] = find(line2);
for k = 1 : length(r1)
distances = sqrt(((r1(k) - r2) .^ 2) + ((c1(k) - c2) .^ 2));
[minDistance, index] = min(distances);
% Find the midPoint
midX(k) = mean([c1(k), c2(index)]);
midY(k) = mean([r1(k), r2(index)]);
% Burn into mask
mask(round(midY(k)), round(midX(k))) = true;
end
% Need to add a small amount of noise to x to make the values unique.
midX = midX + 0.001 * rand(size(midX));
midY = midY + 0.001 * rand(size(midY));
% Interpolate x and y to make sure there are no gaps.
kVec = 1 : length(midX);
kFit = linspace(1, kVec(end), 10000);
xFit = interp1(kVec, midX, kFit, 'linear');
yFit = interp1(kVec, midY, kFit, 'linear');
% Remove duplicate values
xy = unique(round([xFit(:), yFit(:)]), "rows");
% Extract individual x and y.
midX = xy(:, 1);
midY = xy(:, 2);
hold on;
plot(midX, midY, 'g.', 'MarkerSize', 10);
