迷宫路线寻找算法的matlab仿真

1.问题描述：

迷宫创建算法和迷宫路径寻找算法

2.部分程序：

% Clean up.
 clc; 
 close all; 
 clear all; 
 fontSize = 20;  % Font size for image captions.% Change the current folder to the folder of this m-file.
 % (The line of code below is from Brett Shoelson of The Mathworks.)
 if(~isdeployed)
     cd(fileparts(which(mfilename)));
 end
     
 % For convenience in browsing, set a starting folder from which to browse.
 startingFolder = 'C:\Documents and Settings\tk2013\My Documents\My Pictures\MISC\Mazes';
 if ~exist(startingFolder, 'dir')
     % If that folder doesn't exist, just start in the current folder.
     startingFolder = pwd;
 endcontinueWithAnother = true;
 promptMessage = sprintf('Please specify a maze image (in the next window).\nThis program will attempt to solve the maze.');
 button = questdlg(promptMessage, 'maze_solution', 'OK', 'Cancel', 'OK');
 if strcmpi(button, 'Cancel')
     continueWithAnother = false;
 endwhile continueWithAnother
     % Get the name of the maze image file that the user wants to use.
     defaultFileName = fullfile(startingFolder, '*.*');
     [baseFileName, folder] = uigetfile(defaultFileName, 'Select maze image file');
     if baseFileName == 0
         % User hit cancel.  Bail out.
         return;
     end
     fullFileName = fullfile(folder, baseFileName);     % Here are some hard coded file names for ease in developing and debugging,
     % so we don't have to use uigetfile() all the time.    % Gotten from http://www.erclc.org/StaffPages/David/Mazes/Maze1.gif
     % This maze works fine.
     % fullFileName = fullfile(folder, 'Maze1.gif');    % Gotten from http://www.mattneuman.com/maze.htm
     % This is a test maze that won't work because it is not a "non-perfect maze."
     % fullFileName = fullfile(folder, 'Maze of Sisyphus.gif');    % Open the maze image file.
     originalImage = imread(fullFileName);
     [rows cols numberOfColorBands] = size(originalImage);    % Convert to monochrome for processing.
     if numberOfColorBands > 1
         % Convert to monochrome.
         redPlane = originalImage(:, :, 1);
         greenPlane = originalImage(:, :, 2);
         bluePlane = originalImage(:, :, 3);
         % Find the standard deviation of each color channel.
         redStdDev = std(single(redPlane(:)));
         greenStdDev = std(single(greenPlane(:)));
         blueStdDev = std(single(bluePlane(:)));
         % Take the color channel with the highest contrast.
         % Transfer it into a monochrome image.  This will be the one that we use.
         if redStdDev >= greenStdDev && redStdDev >= blueStdDev
             % Red has most contrast - use that channel.
             monoImage = single(redPlane);
         elseif greenStdDev >= redStdDev && greenStdDev >= blueStdDev
             % Green has most contrast - use that channel.
             monoImage = single(greenPlane);
         else
             % Blue has most contrast - use that channel.
             monoImage = single(bluePlane);
         end
     else
         monoImage = single(originalImage);
     end
     % Now we have a monochrome image that we can use to solve the maze.
     % Display the results of this step.
     close all;    % Close any prior windows that are open from a prior run.
     subplot(2, 2, 1);
     imshow(monoImage, []);
     title('Original Image', 'FontSize', fontSize);
     set(gcf, 'Position', get(0,'Screensize')); % Maximize figure.    % Scale image to 0-255.
     maxValue = max(max(monoImage));
     minValue = min(min(monoImage));
     monoImage = uint8(255 * (single(monoImage) - minValue) / (maxValue - minValue));
     % Threshold to get the walls.  This will also sharpen up blurry, fuzzy wall edges.
     thresholdValue = uint8((maxValue + minValue) / 2);
     binaryImage = 255 * (monoImage < thresholdValue);
     % Display the results of this step.
     subplot(2, 2, 2);
     imshow(binaryImage, []);
     title('Binary Image - The walls are white here, instead of black', 'FontSize', fontSize);    % Label the image to identify discrete, separate walls.
     [labeledImage numberOfWalls] = bwlabel(binaryImage, 4);     % Label each blob so we can make measurements of it
     coloredLabels = label2rgb (labeledImage, 'hsv', 'k', 'shuffle'); % pseudo random color labels
     % Display the results of this step.
     subplot(2, 2, 3);
     imshow(coloredLabels); 
     caption = sprintf('Labeled image of the %d walls, each a different color', numberOfWalls);
     title(caption, 'FontSize', fontSize);
     if numberOfWalls ~= 2
         message = sprintf('This is not a "perfect maze" with just 2 walls.\nThis maze appears to have %d walls,\nso you may get unexpected results.', numberOfWalls);
         uiwait(msgbox(message));
     end

3.仿真结论：

C67