MATLAB: How to start this problem

2dhomeworkmonte carlorandom walks

We consider again the one-dimensional version of the drunkard problem. This time he starts out at position x (e.g., x=10), and takes unit steps left or right with equal probability. Suppose at 0 and a (a>x>0, e.g., a=30) are two bars. When he reaches either one, he is trapped forever.

We want to determine the average time t (the mean number of steps) before the drunkard is trapped. This is a diffusion problem and the 'time' t is called the first passage time. Do a simulation to compute t. (Again note that only the average of t has a meaning and it is that average that we want to compute.)

Best Answer

See my attached collection of random walk programs/demos I've written. Adapt as needed.

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MATLAB: Adding Noise to the Image

Try this:

clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
imtool close all;  % Close all imtool figures.
clear;  % Erase all existing variables.
workspace;  % Make sure the workspace panel is showing.
format longg;
format compact;
fontSize = 20;
%===============================================================================
% Read in a standard MATLAB gray scale demo image.
folder = fileparts(which('cameraman.tif')); % Determine where demo folder is (works with all versions).
baseFileName = 'cameraman.tif';
% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);
% Check if file exists.
if ~exist(fullFileName, 'file')
  % File doesn't exist -- didn't find it there.  Check the search path for it.
  fullFileNameOnSearchPath = baseFileName; % No path this time.
  if ~exist(fullFileNameOnSearchPath, 'file')
    % Still didn't find it.  Alert user.
    errorMessage = sprintf('Error: %s does not exist in the search path folders.', fullFileName);
    uiwait(warndlg(errorMessage));
    return;
  end
end
grayImage = imread(fullFileName);
% Get the dimensions of the image.  
% numberOfColorBands should be = 1.
[rows, columns, numberOfColorBands] = size(grayImage);
if numberOfColorBands > 1
  % It's not really gray scale like we expected - it's color.
  % Convert it to gray scale by taking only the green channel.
  grayImage = grayImage(:, :, 2); % Take green channel.
end
% Display the original gray scale image.
subplot(1, 2, 1);
imshow(grayImage, []);
title('Original Grayscale Image', 'FontSize', fontSize);
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0 0 1 1]);
% Give a name to the title bar.
set(gcf, 'Name', 'Demo by ImageAnalyst', 'NumberTitle', 'Off') 
% Initialize an output image.
noisyImage = grayImage; % Initialize
% Get 5,000 random locations
noiseIndexes = randperm(numel(grayImage), 5000);
% Add noise
noisyImage(noiseIndexes) = 255;
% Display the noisy image.
subplot(1, 2, 2);
imshow(noisyImage, []);
title('Noisy Image', 'FontSize', fontSize);
axis on;

MATLAB: Hi, can any one help me here how to create a binary mask (automatically) remove the foreground information of the input image

Try this for starters, and tweak as needed.

clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
clear;  % Erase all existing variables. Or clearvars if you want.
workspace;  % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 20;
% Get the base filename.
baseFileName = 'segmented.jpg'; % Assign the one on the button that they clicked on.
% Get the full filename, with path prepended.
folder = pwd; % Current folder
fullFileName = fullfile(folder, baseFileName);
% Check if file exists.
if ~exist(fullFileName, 'file')
  % File doesn't exist -- didn't find it there.  Check the search path for it.
  fullFileNameOnSearchPath = baseFileName; % No path this time.
  if ~exist(fullFileNameOnSearchPath, 'file')
    % Still didn't find it.  Alert user.
    errorMessage = sprintf('Error: %s does not exist in the search path folders.', fullFileName);
    uiwait(warndlg(errorMessage));
    return;
  end
end
% Read in image.
originalImage = imread(fullFileName);
% Get the dimensions of the image.
% numberOfColorBands should be = 1.
[rows, columns, numberOfColorBands] = size(originalImage);
if numberOfColorBands > 1
  % It's not really gray scale like we expected - it's color.
  % Convert it to gray scale by taking only the blue channel.
  grayImage = min(originalImage, [], 3); % Take blue channel.
else
  % It's already grayscale
  grayImage = originalImage;
end
% Display the original image.

subplot(2, 3, 1);
imshow(originalImage);
axis on;
title('Original Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Display the original image.
subplot(2, 3, 2);
% Crop off white surround.
grayImage = grayImage(74:465, 430:851);
imshow(grayImage, []);
axis on;
title('Gray Scale Image', 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
hp = impixelinfo(); % Let user ouse around over image and get gray levels.
% Set up figure properties:
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0 0 1 1]);
% Get rid of tool bar and pulldown menus that are along top of figure.
set(gcf, 'Toolbar', 'none', 'Menu', 'none');
% Give a name to the title bar.
set(gcf, 'Name', 'Demo by ImageAnalyst', 'NumberTitle', 'Off')
drawnow;
% Let's compute and display the histogram.
subplot(2, 3, 3);
histogram(grayImage);
xlim([0, 255]);
grid on;
title('Intensity Histogram of Gray Scale Image', 'FontSize', fontSize, 'Interpreter', 'None');
xlabel('Gray Level', 'FontSize', fontSize);
ylabel('Pixel Count', 'FontSize', fontSize);
% Need to get the background (light stuff) but not get any light stuff in the bottle.
% Threshold to find dark.
binaryImage = grayImage > 80 & grayImage < 160;
% Extract the largest blob only
binaryImage = bwareafilt(binaryImage, 1);
% Fill any holes.
% binaryImage = imfill(binaryImage, 'holes');
% Invert to get the holes.
binaryImage = ~binaryImage;
% Extract the two largest blobs
binaryImage = bwareafilt(binaryImage, 2);
% Display the binary image.


subplot(2, 3, 4);
imshow(binaryImage, []);
axis on;
title('Binary Background Image', 'FontSize', fontSize);
% Display the binary image.
subplot(2, 3, 5);
imshow(~binaryImage, []);
% Invert and remove blobs touching border.
binaryImage = imclearborder(~binaryImage, 4);
% Extract the largest blob
binaryImage = bwareafilt(binaryImage, 1);
% Display the binary image.
subplot(2, 3, 5);
imshow(binaryImage, []);
axis on;
title('Binary Background Image', 'FontSize', fontSize);

Best Answer

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MATLAB: Adding Noise to the Image

MATLAB: Hi, can any one help me here how to create a binary mask (automatically) remove the foreground information of the input image

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