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Yearly Archives: 2014
Basic MATLAB
Using the break command to stop the while loop for given condition
t = 1; while 1 % infinite loop t = t+1; if (t > 1000 ) % condition break % break the loop end end
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Vehicle detection, blob analysis
clc; clear all; close all;
% Read a grayscale or color image from the file img = imread('car3.jpg'); % Display the grayscale image I figure(1) imshow(img)
Convert the grayscale image I to a binary image
bwi = im2bw(img, graythresh(img));
bwi =~bwi; % As bacground is light its better to inverse the image
figure(2)
imshow(bwi)
Remove from a binary image all connected components (objects) that have fewer than 100 pixels.do some adjsutements based on image
bwi = bwareaopen(bwi,100); figure(3); imshow(bwi); % Create morphological structuring element, something which resemples the % blob str = strel('square',20); bw = imdilate(bwi,str);
Trace region boundaries in binary image, As you see there might be some false detections.
[B,L] = bwboundaries(bw,'noholes'); figure(4); imshow(img); hold on for i = 1:length(B) plot(B{i}(:,2), B{i}(:,1), 'r', 'LineWidth', 2.5) end
World Magnetic Model,Matlab
close all;clear all;clc; height = 500000; % A scalar value, in meters lat = -90:2.5:90; % geodetic latitude, in degrees, where north latitude is %positive, and south latitude is negative lon = -180:2.5:180; % geodetic longitude, in degrees, %where east longitude is positive,and west longitude is negative % dyearA scalar decimal year. Decimal year is the desired year in %a decimal format to include any fraction of the year that has already passed. sla = size(lat); sln = size(lon); for i = 1:sla(2) for j =1:sln(2) [Bxyz, h, dec, dip, f] = ... wrldmagm(height, lat(i), lon(j), decyear(2014,1,22),'2010'); % Note that WMM-2010 isvalid from January 1, 2010, until December 31, % 2014 % Bxyz Magnetic field vector in nanotesla (nT) % h Horizontal intensity in nanotesla (nT) % dec Declination in degrees % dip Inclination in degrees % f Total intensity in nanotesla (nT) Bx(i,j) = Bxyz(1,1); By(i,j) = Bxyz(2,1); Bz(i,j) = Bxyz(3,1); Bm(i,j) = f; % [Bxyz(i,j), h(i,j), dec(i,j), dip(i,j), f(i,j)] = ... % wrldmagm(height, lat(i), lon(j), decyear(2014,1,22),'2010'); end end
Z component
xwidth = 640; ywidth = 320; colormap jet hFig = figure(1); contourf(lon,lat,Bz) hold on set(gcf,'PaperPositionMode','auto') set(hFig, 'Position', [100 100 xwidth ywidth]) axis([-180 180 -90 90]) colorbar load('topo.mat','topo','topomap1') contour(0:179,-90:89,topo(:,1:180),[0 0],'.k') contour(-180:-1,-90:89,topo(:,181:360),[0 0],'.k') ylabel('Latitude [deg]') xlabel('Longitude [deg]') title('World Magnetic Model, Bz(nT) at Alt = 500 km')
Component X
hFig = figure(2); contourf(lon,lat,Bx) hold on set(gcf,'PaperPositionMode','auto') set(hFig, 'Position', [100 100 xwidth ywidth]) axis([-180 180 -90 90]) colorbar load('topo.mat','topo','topomap1') contour(0:179,-90:89,topo(:,1:180),[0 0],'.k') contour(-180:-1,-90:89,topo(:,181:360),[0 0],'.k') ylabel('Latitude [deg]') xlabel('Longitude [deg]') title('World Magnetic Model, Bx(nT) at Alt = 500 km')
Component Y
hFig = figure(3); contourf(lon,lat,By) hold on set(gcf,'PaperPositionMode','auto') set(hFig, 'Position', [100 100 xwidth ywidth]) axis([-180 180 -90 90]) colorbar load('topo.mat','topo','topomap1') contour(0:179,-90:89,topo(:,1:180),[0 0],'.k') contour(-180:-1,-90:89,topo(:,181:360),[0 0],'.k') ylabel('Latitude [deg]') xlabel('Longitude [deg]') title('World Magnetic Model, By(nT) at Alt = 500 km')
Total intensity in nanotesla (nT)
hFig = figure(4); contourf(lon,lat,Bm) hold on set(gcf,'PaperPositionMode','auto') set(hFig, 'Position', [100 100 xwidth ywidth]) axis([-180 180 -90 90]) colorbar load('topo.mat','topo','topomap1') contour(0:179,-90:89,topo(:,1:180),[0 0],'.k') contour(-180:-1,-90:89,topo(:,181:360),[0 0],'.k') ylabel('Latitude [deg]') xlabel('Longitude [deg]') title('World Magnetic Model, Total intensity(nT) at Alt = 500 km')
Distance Transform Path Planning Algorithm
clc;close all;clear all;
Input Map
RGB = imread('Mapn.png'); figure('Position',[600 0 600 1000],'color','k'); image(RGB); hold on; axis off axis image hold off; % Convert to binary image matrix and inverse matrix values I = rgb2gray(RGB); binaryImage = im2bw(RGB, 0.3); binaryImage = 1-binaryImage; % Inital pose xs = 540; ys = 750; % Goal Pose xg = 150; yg = 150;
Distance to Goal
sz = size(binaryImage); for i = 1:sz(1) for j = 1:sz(2) rg(i,j) = sqrt((i-yg)^2 +(j - xg)^2); end end % Pose Matrix pose = zeros(sz(1),sz(2)); pose(ys,xs) = 1; pose(yg,xg) = 1;
Di = 15; % Distance of influence of the obstacles % Compute for every pixel the distance to the nearest obstacle(non zero % elements which after inversion corespondent to the obstacles) [D,IDX] = bwdist(binaryImage); for i = 1:sz(1) for j = 1:sz(2) rd = D(i,j); if (rd <= Di) rg(i,j) = 1e6; end end end
Distance Transform Path Planning Algorithm
figure('Position',[600 0 600 1000],'color','k'); hold on; image(RGB); colormap gray contour(rg,15); spy(pose,'*r'); axis off axis image title('Distance Transform Path Planning Algorithm','color','w'); x = xs; y = ys; last = rg(y-1,x-1); while (x ~= xg)||(y ~= yg) dis =[ rg(y-1,x-1), rg(y-1,x),rg(y-1,x+1); rg(y,x-1), rg(y,x) ,rg(y,x+1); rg(y+1,x-1), rg(y+1,x),rg(y+1,x+1)]; m = min(dis(:)); [r,c] = find(dis == m); rg(y,x) = 1E6; y = y-2+r; x = x-2+c; pose(y,x) = 1; end spy(pose,'.r'); set(gcf, 'InvertHardCopy', 'off'); hold off;
Small Satellites 