matlab 在图像处理中常用的函数使用（1）

<span style="font-size:18px;">tic; % Start timer.
clc; % Clear command window.
clearvars; % Get rid of variables from prior run of this m-file.
fprintf('Running BlobsDemo.m...\n'); % Message sent to command window.
workspace; % Make sure the workspace panel with all the variables is showing.
imtool close all;  % Close all imtool figures.
format long g;
format compact;
captionFontSize = 14;

% Check that user has the Image Processing Toolbox installed.
hasIPT = license('test', 'image_toolbox');
if ~hasIPT
	% User does not have the toolbox installed.
	message = sprintf('Sorry, but you do not seem to have the Image Processing Toolbox.\nDo you want to try to continue anyway?');
	reply = questdlg(message, 'Toolbox missing', 'Yes', 'No', 'Yes');
	if strcmpi(reply, 'No')
		% User said No, so exit.
		return;
	end
end

% Read in a standard MATLAB demo image of coins (US nickles and dimes, which are 5 cent and 10 cent coins)
baseFileName = 'coins.png';
folder = fileparts(which(baseFileName)); % Determine where demo folder is (works with all versions).
fullFileName = fullfile(folder, baseFileName);
if ~exist(fullFileName, 'file')
	% It doesn't exist in the current folder.
	% Look on the search path.
	if ~exist(baseFileName, 'file')
		% It doesn't exist on the search path either.
		% Alert user that we can't find the image.
		warningMessage = sprintf('Error: the input image file\n%s\nwas not found.\nClick OK to exit the demo.', fullFileName);
		uiwait(warndlg(warningMessage));
		fprintf(1, 'Finished running BlobsDemo.m.\n');
		return;
	end
	% Found it on the search path.  Construct the file name.
	fullFileName = baseFileName; % Note: don't prepend the folder.
end
% If we get here, we should have found the image file.
originalImage = imread(fullFileName);
% Check to make sure that it is grayscale, just in case the user substituted their own image.
[rows, columns, numberOfColorChannels] = size(originalImage);
if numberOfColorChannels > 1
	promptMessage = sprintf('Your image file has %d color channels.\nThis demo was designed for grayscale images.\nDo you want me to convert it to grayscale for you so you can continue?', numberOfColorChannels);
	button = questdlg(promptMessage, 'Continue', 'Convert and Continue', 'Cancel', 'Convert and Continue');
	if strcmp(button, 'Cancel')
		fprintf(1, 'Finished running BlobsDemo.m.\n');
		return;
	end
	% Do the conversion using standard book formula
	originalImage = rgb2gray(originalImage);
end

% Display the grayscale image.
subplot(3, 3, 1);
imshow(originalImage);
%%
% Maximize the figure window.
set(gcf, 'units','normalized','outerposition',[0 0 1 1]);
% Force it to display RIGHT NOW (otherwise it might not display until it's all done, unless you've stopped at a breakpoint.)
drawnow;
caption = sprintf('Original "coins" image showing\n6 nickels (the larger coins) and 4 dimes (the smaller coins).');
title(caption, 'FontSize', captionFontSize);
axis image; % Make sure image is not artificially stretched because of screen's aspect ratio.
%%
% Just for fun, let's get its histogram and display it.
[pixelCount, grayLevels] = imhist(originalImage);
subplot(3, 3, 2);
bar(pixelCount);
title('Histogram of original image', 'FontSize', captionFontSize);
xlim([0 grayLevels(end)]); % Scale x axis manually.
grid on;
%%
% Threshold the image to get a binary image (only 0's and 1's) of class "logical."
% Method #1: using im2bw()
%   normalizedThresholdValue = 0.4; % In range 0 to 1.
%   thresholdValue = normalizedThresholdValue * max(max(originalImage)); % Gray Levels.
%   binaryImage = im2bw(originalImage, normalizedThresholdValue);       % One way to threshold to binary
% Method #2: using a logical operation.
thresholdValue = 100;
binaryImage = originalImage > thresholdValue; % Bright objects will be chosen if you use >.
% ========== IMPORTANT OPTION ============================================================
% Use < if you want to find dark objects instead of bright objects.
%   binaryImage = originalImage < thresholdValue; % Dark objects will be chosen if you use <.

% Do a "hole fill" to get rid of any background pixels or "holes" inside the blobs.
binaryImage = imfill(binaryImage, 'holes');

% Show the threshold as a vertical red bar on the histogram.
hold on;
maxYValue = ylim;
line([thresholdValue, thresholdValue], maxYValue, 'Color', 'r');
% Place a text label on the bar chart showing the threshold.
annotationText = sprintf('Thresholded at %d gray levels', thresholdValue);
% For text(), the x and y need to be of the data class "double" so let's cast both to double.
text(double(thresholdValue + 5), double(0.5 * maxYValue(2)), annotationText, 'FontSize', 10, 'Color', [0 .5 0]);
text(double(thresholdValue - 70), double(0.94 * maxYValue(2)), 'Background', 'FontSize', 10, 'Color', [0 0 .5]);
text(double(thresholdValue + 50), double(0.94 * maxYValue(2)), 'Foreground', 'FontSize', 10, 'Color', [0 0 .5]);

% Display the binary image.
subplot(3, 3, 3);
imshow(binaryImage); 
title('Binary Image, obtained by thresholding', 'FontSize', captionFontSize); </span>