MATLAB custom datatip in images - matlab

Following the instructions on other pages, e.g.
http://blogs.mathworks.com/videos/2011/10/19/tutorial-how-to-make-a-custom-data-tip-in-matlab/
http://it.mathworks.com/help/matlab/ref/datacursormode.html
http://it.mathworks.com/matlabcentral/answers/68079-how-to-add-additional-info-to-the-data-cursor
i've written a custom callback function for the datatip to show me the index of the points on a x-y graph as well as their x and y coordinates:
function output_txt = customCallback_DataTip(obj,event_obj)
% Display the position of the data cursor
% obj Currently not used (empty)
% event_obj Handle to event object
% output_txt Data cursor text string (string or cell array of strings).
pos = get(event_obj,'Position');
output_txt = {['X: ',num2str(pos(1),4)],...
['Y: ',num2str(pos(2),4)]};
% If there is a Z-coordinate in the position, display it as well
if length(pos) > 2
output_txt{end+1} = ['Z: ',num2str(pos(3),4)];
else % 2D plot: write index of current point
i = find(event_obj.Target.XData == pos(1), 1);
output_txt{end+1} = ['i: ',num2str(i)];
end
This code starts from the default callback suggested by MATLAB, and adds a z-coordinate info whenever the plot is a 3D one. Since I very often need to know the array index of a point on a graph, the custom callback function is enabled automatically at MATLAB startup.
Now, whenever I plot an image (e.g. via imagesc) I would like to have the "normal" image datatip:
i.e. with Index/RGB information on it. How can I modify the callback function in order to obtain this behavior?
EDIT: i would like to modify my custom callback so that it automatically displays something similar to the default MATLAB default datatip when I'm using the datatip on an image.

To accomplish this, you can check the type of the event_obj.Target and respond accordingly.
get(event_obj.Target, 'type')
All images (whether imagesc, image, or imshow) will have a Type of image.
isImage = strcmpi(get(event_obj.Target, 'type'), 'image')
You can then extract the image data. If you have an indexed image, you can also get the colormap to determine all the other information to go into the datatip.
cdata = get(event_obj.Target, 'cdata');
cmap = colormap(ancestor(event_obj.Target, 'axes'));
Bringing this all together, I would modify your custom data tip callback to be something like this.
function output_txt = callback(obj, event_obj, clims)
% Get the cursor location
pos = get(event_obj, 'Position');
output_txt = {sprintf('[X,Y]: [%i, %i]', pos(1), pos(2))};
if strcmpi(get(event_obj.Target, 'type'), 'image')
% Get the image data
cdata = get(event_obj.Target, 'CData');
% Check to ensure pos is in range
if pos(1) < 1 || pos(1) > size(cdata, 2) || ...
pos(2) < 1 || pos(2) > size(cdata, 1)
rgb = {NaN, NaN, NaN};
newline = sprintf('[R,G,B]: [%0.4f %0.4f %0.4f]', rgb{:});
output_txt = cat(1, output_txt, newline);
return
end
% If the image is RGB
if size(cdata, 3) == 3
rgb = num2cell(cdata(pos(2), pos(1), :));
% If this is an indexed image
else
index = cdata(pos(2), pos(1));
% Figure out the colormap
hax = ancestor(event_obj.Target, 'axes');
cmap = colormap(hax);
% If the CData is scaled, we need to scale to the colormap
if strcmpi(get(event_obj.Target, 'CDataMapping'), 'scaled')
value = (index - clims(1)) * size(cmap, 1) / diff(clims);
else
value = index;
end
% Determine RGB value from colormap
rgb = num2cell(ind2rgb(round(value), cmap));
if round(index) == index
newline = sprintf('Index: %d', index);
else
newline = sprintf('Index: %.4f', index);
end
% Generate datatip text
output_txt = cat(1, output_txt, newline);
end
output_txt = cat(1, output_txt, ...
sprintf('[R,G,B]: [%0.4f %0.4f %0.4f]', rgb{:}));
% Otherwise we use your custom datatip for plots
else
index = find(event_obj.Target.XData == pos(1), 1);
pos = get(event_obj, 'Position');
output_txt = { sprintf('X: %0.4f', pos(1));
sprintf('Y: %0.4f', pos(2))};
% If there is a Z-coordinate in the position, display it as well
if length(pos) > 2
output_txt{end+1} = sprintf('Z: %0.4f', pos(3));
else % 2D plot: write index of current point
output_txt{end+1} = sprintf('i: %d', index);
end
end
end
If you notice, I'm passing in an additional variable (clims) to the callback function. This is because some versions won't actually allow me to query axes properties from within the datatip UpdateFcn. So this means that you will have to change your UpdateFcn anonymous function just a little bit.
h = datacursormode(fig);
set(h, 'Enable', 'on')
% Here I have to pass the `clims` because I can't fetch them inside
set(h, 'UpdateFcn', #(dt,e)callback(dt, e, caxis(ancestor(dt.Host, 'axes'))));
Using this, I was able to show the proper display for both plots and images (both indexed and RGB).

Related

How to cut part of the data out of a plot in Matlab

I just wanted to cut part of my data out in MATLAB, for example:
If I click on two points on the axis, it will cut the elements after the I click on with respect to the x-axis. I will post my code and a pic for further details
Thank you in advance
load sample.mat
X = sample.current;
X1 = sample.voltage;
Ts = 0.01;
Fs = 1/Ts;
Fm = Fs/2;
Fc = 2;
N =10;
d = fdesign.lowpass('N,Fc',N,Fc,Fs);
designmethods(d);
Hd = design(d);
%fvtool(Hd)
%X is a variable form csv
%X1 is a variable from csv
output = filter(Hd,X);
output1 = filter(Hd,X1);
figure;
plot(X,X1,'-g');
hold on
plot(output, output1,'r');
hold off
legend('raw signal','filtered signal')
grid on
x = output, output1;
y = output1;
figure
subplot(2,1,1)
plot(x,y,'r');
title('Original plot');
uiwait(msgbox('Select an x-value from which to crop','modal'));
[x_user ~] = ginput(1); % Let the user select an x-value from which to crop.
x(x>x_user) = [];
subplot(2,1,2);
plot(x,y,'r');
title('New plot with cropped values');
xlim([min(x(:)) max(x(:))]);
enter image description here
*Posting this as an answer to format code.
If its only one graphic you can just select the points that you want to delete using the "Brush/Select Data" (icon of a brush with a red square located at the menubar of the figure) selecting the data you want to be gone and then pressing the delete key.
If you want to do it with code you can try to find the index of the point where the signal starts to decrease over the X using something like:
% Find the index where X starts to decrease
maxIndex = find(data.x == max(data.x));
% In case of multiple indexs, ensure we get the first one
maxIndex = maxIndex(1);
% Copy data to new vector
saveData.x = data.x(1:maxIndex);
saveData.y = data.y(1:maxIndex);
If you want to use the users' click position you can use find to locate the index of the first element after the click:
% Get the coords of the first click
userFirstClick = ginput(1);
% Get the X component of the coords
xCoordInit = userFirstClick(1);
% Locate the index of the first element that is greater than
% the xCoord
firstXIndex = find(data.x >= xCoordInit);
% In case of multiple indexs, ensure we get the first one
firstXIndex = firstXIndex(1);
% Do the same to get the final index
userSecondClick = ginput(1);
xCoordFinal = userSecondClick(1);
finalXIndex = find(data.x > xCoordFinal);
finalXIndex = finalXIndex(1)-1;
% -1 because data.x(finalXIndex) is already greater than xCoordFinal
% Copy data to the new vector
saveData.x = data.x(firstXIndex:finalXIndex);
saveData.y = data.y(firstXIndex:finalXIndex);
Then just plot saveData.
Edit
There was a typo on my previous code, here you have a fully functional example where you just need to click over the two points where you want to crop.
function cropSine()
% create a period of a Sine to initialize our data
data.x = -pi*3:0.01:pi*3;
data.y = sin(data.x);
% we make it loop back just as in your picture
data.x = [data.x,data.x(end:-1:1)];
data.y = [data.y, -data.y*0.5+5];
% create a figure to show the signal we have just created
figure
% create the axes where the data will be displayed
mainAx = axes();
% Draw our fancy sine!
plot(data.x, data.y, 'b-', 'Parent', mainAx);
% Request the initial position to crop
userFirstClick = ginput(1);
% Get the index of the nearest point
initIndex = getNearest(userFirstClick, data);
% Do the same to get the final index
userSecondClick = ginput(1);
% Get the index of the nearest point
finalIndex = getNearest(userSecondClick, data);
% check if its a valid point
if isempty(initIndex) || isempty(finalIndex)
disp('No points in data vector!');
return;
end
% Ensure that final index is greater than first index
if initIndex > finalIndex
tempVal = initIndex;
initIndex = finalIndex;
finalIndex = tempVal;
end
% Copy the data that we want to save into a new variable
saveData.x = data.x(initIndex:finalIndex);
saveData.y = data.y(initIndex:finalIndex);
% Plot the cropped data in red!
hold(mainAx, 'on');
plot(saveData.x, saveData.y, 'r-', 'Parent', mainAx);
hold(mainAx, 'off');
end
function nearestIndex = getNearest(clickPos, vector)
nearestIndex = [];
numPoints = length(vector.x);
if numPoints == 0
return;
end
nearestIndex = 1;
minDist = calcDist(vector.x(1), vector.y(1), clickPos(1), clickPos(2));
for pointID = 1:numPoints
dist = calcDist(vector.x(pointID), vector.y(pointID), clickPos(1), clickPos(2));
if dist < minDist
nearestIndex = pointID;
minDist = dist;
end
end
end
function dist = calcDist(p1x, p1y, p2x, p2y)
dist = sqrt(power(p1x-p2x,2)+power(p1y-p2y,2));
end

moving shadow elimination in video

I wish to remove moving shadow in video. I followed the steps as mentioned in this article, but getting the same result before and after applying threshold operation on the swt output. didn't get the expected output...Can anyone suggest me what I am doing wrong?
Steps to do for shadow removal:
(i) Read the video.
(ii) After the color conversion split the h s v components
(iii) applying the stationary wavelet transform on on s and v components of frame
(iv) calculate skew value for respective swt output of s and v component
(v) Assign the value 1 and 0 to 's and v' pixel if swt of v is greater than skewness value of v likewise for s too.
(vi) Do inverse swt over the s and v
(vii)Combine the h s and v
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.
fontSize = 22;
movieFullFileName = fullfile('cam4v.mp4');
% Check to see that it exists.
if ~exist(movieFullFileName, 'file')
strErrorMessage = sprintf('File not found:\n%s\nYou can choose a new one,
or cancel', movieFullFileName);
response = questdlg(strErrorMessage, 'File not found', 'OK - choose a new
movie.', 'Cancel', 'OK - choose a new movie.');
if strcmpi(response, 'OK - choose a new movie.')
[baseFileName, folderName, FilterIndex] = uigetfile('*.avi');
if ~isequal(baseFileName, 0)
movieFullFileName = fullfile(folderName, baseFileName);
else
return;
end
else
return;
end
end
try
videoObject = VideoReader(movieFullFileName);
% Determine how many frames there are.
numberOfFrames = videoObject.NumberOfFrames;
vidHeight = videoObject.Height;
vidWidth = videoObject.Width;
numberOfFramesWritten = 0;
% Prepare a figure to show the images in the upper half of the screen.
figure;
% screenSize = get(0, 'ScreenSize');
% Enlarge figure to full screen.
set(gcf, 'units','normalized','outerposition',[0 0 1 1]);
% Ask user if they want to write the individual frames out to disk.
promptMessage = sprintf('Do you want to save the individual frames out to
individual disk files?');
button = questdlg(promptMessage, 'Save individual frames?', 'Yes', 'No',
'Yes');
if strcmp(button, 'Yes')
writeToDisk = true;
% Extract out the various parts of the filename.
[folder, baseFileName, extentions] = fileparts(movieFullFileName);
% Make up a special new output subfolder for all the separate
% movie frames that we're going to extract and save to disk.
% (Don't worry - windows can handle forward slashes in the folder
name.)
folder = pwd; % Make it a subfolder of the folder where this m-file
lives.
outputFolder = sprintf('%s/Movie Frames from %s', folder,
baseFileName);
% Create the folder if it doesn't exist already.
if ~exist(outputFolder, 'dir')
mkdir(outputFolder);
end
else
writeToDisk = false;
end
% Loop through the movie, writing all frames out.
% Each frame will be in a separate file with unique name.
for frame = 1 : numberOfFrames
% Extract the frame from the movie structure.
thisFrame = read(videoObject, frame);
% Display it
hImage = subplot(2, 2, 1);
image(thisFrame);
caption = sprintf('Frame %4d of %d.', frame, numberOfFrames);
title(caption, 'FontSize', fontSize);
drawnow; % Force it to refresh the window.
% Write the image array to the output file, if requested.
if writeToDisk
% Construct an output image file name.
outputBaseFileName = sprintf('Frame %4.4d.png', frame);
outputFullFileName = fullfile(outputFolder, outputBaseFileName);
% Stamp the name and frame number onto the image.
% At this point it's just going into the overlay,not actually
getting written into the pixel values.
text(5, 15, outputBaseFileName, 'FontSize', 20);
% Extract the image with the text "burned into" it.
frameWithText = getframe(gca);
% frameWithText.cdata is the image with the text
% actually written into the pixel values.
% Write it out to disk.
imwrite(frameWithText.cdata, outputFullFileName, 'png');
end
if frame == 1
xlabel('Frame Number');
ylabel('Gray Level');
% Get size data later for preallocation if we read
% the movie back in from disk.
[rows, columns, numberOfColorChannels] = size(thisFrame);
end
% Update user with the progress. Display in the command window.
if writeToDisk
progressIndication = sprintf('Wrote frame %4d of %d.', frame,
numberOfFrames);
else
progressIndication = sprintf('Processed frame %4d of %d.', frame,
numberOfFrames);
end
disp(progressIndication);
% Increment frame count (should eventually = numberOfFrames
% unless an error happens).
numberOfFramesWritten = numberOfFramesWritten + 1;
% Now let's do the differencing
alpha = 0.5;
if frame == 1
Background = thisFrame;
else
% Change background slightly at each frame
% Background(t+1)=(1-alpha)*I+alpha*Background
Background = (1-alpha)* thisFrame + alpha * Background;
end
% Display the changing/adapting background.
subplot(2, 2, 3);
imshow(Background);
title('Adaptive Background', 'FontSize', fontSize);
% Do color conversion from rgb to hsv
x=rgb2hsv(thisFrame);
y=rgb2hsv(Background);
% Split the hsv component to h,s,v value
Hx = x(:,:,1); Hy = y(:,:,1);
Sx = x(:,:,2); Sy = y(:,:,2);
Vx = x(:,:,3); Vy = y(:,:,3);
%Find the absolute diffrence between h s v value of current and
previous frame
dh=(abs(double(Hx) - double(Hy)));
ds1=(abs(double(Sx) - double(Sy)));
dv1=(abs(double(Vx) - double(Vy)));
%Perform the swt2 transformation on difference of s and v value
[as,hs,vs,ds] = swt2(ds1,1,'haar');
[av,hv,vv,dv] = swt2(dv1,1,'haar');
%Compute the skewness value of 'swt of v'
sav=skewness(av(:));
shv=skewness(hv(:));
svv=skewness(vv(:));
sdv=skewness(dv(:));
%Compute the skewness value of 'swt of s'
sas=skewness(as(:));
shs=skewness(hs(:));
svs=skewness(vs(:));
sds=skewness(ds(:));
% Do the shadow detection based on the output of swt and skew of 'v'
value
% Compare swt v output with its skew value if the av >=sav then av is
assigned to one else it becomes zero.This operation continues till variable i
b=(av>=sav); f= (as>=sas);
c=(hv>=shv); g=(hs>=shs);
d=(vv>=svv); h=(vs>=svs);
e=(dv>=sdv); i=(ds>=sds);
% Remove the shadows based on 'and operation
j=(b&f); l=(d&h);
k=(c&g); m=(e&i);
% Do inverse swt operation
recv = iswt2(b,c,d,e,'haar');
recs= iswt2(j,k,l,m,'haar');
%Combine the value of h,s and v
de_shadow=cat(3,dh,recs,recv);
rgb=hsv2rgb(de_shadow);
% Plot the image.
subplot(2, 2, 4);
imshow(rgb);
title('output Image', 'FontSize', fontSize);
end
% Alert user that we're done.
if writeToDisk
finishedMessage = sprintf('Done! It wrote %d frames to
folder\n"%s"', numberOfFramesWritten, outputFolder);
else
finishedMessage = sprintf('Done! It processed %d frames of\n"%s"',
numberOfFramesWritten, movieFullFileName);
end
disp(finishedMessage); % Write to command window.
uiwait(msgbox(finishedMessage)); % Also pop up a message box.
% Exit if they didn't write any individual frames out to disk.
if ~writeToDisk
return;
end
% Ask user if they want to read the individual frames from the disk,
% that they just wrote out, back into a movie and display it.
promptMessage = sprintf('Do you want to recall the individualframes\nback
from disk into a movie?\n(This will take several seconds.)');
button = questdlg(promptMessage, 'Recall Movie?', 'Yes', 'No', 'Yes');
if strcmp(button, 'No')
return;
end
% Create a VideoWriter object to write the video out to a new, different
file.
writerObj = VideoWriter('Newcam4v.mp4');
open(writerObj);
% Read the frames back in from disk, and convert them to a movie.
% Preallocate recalledMovie, which will be an array of structures.
% First get a cell array with all the frames.
allTheFrames = cell(numberOfFrames,1);
allTheFrames(:) = {zeros(vidHeight, vidWidth, 3, 'uint8')};
% Next get a cell array with all the colormaps.
allTheColorMaps = cell(numberOfFrames,1);
allTheColorMaps(:) = {zeros(256, 3)};
% Now combine these to make the array of structures.
recalledMovie = struct('cdata', allTheFrames, 'colormap',allTheColorMaps)
for frame = 1 : numberOfFrames
% Construct an output image file name.
outputBaseFileName = sprintf('Frame %4.4d.png', frame);
outputFullFileName = fullfile(outputFolder, outputBaseFileName);
% Read the image in from disk.
thisFrame = imread(outputFullFileName);
% Convert the image into a "movie frame" structure.
thisFrame=imresize(thisFrame,[452, 231]);
recalledMovie(frame) = im2frame(thisFrame);
% Write this frame out to a new video file.
writeVideo(writerObj, thisFrame);
end
close(writerObj);
% Get rid of old image and plot.
delete(hImage);
% Create new axes for our movie.
subplot(1, 3, 2);
axis off; % Turn off axes numbers.
title('Movie recalled from disk', 'FontSize', fontSize);
% Play the movie in the axes.
movie(recalledMovie);
% Note: if you want to display graphics or text in the overlay
% as the movie plays back then you need to do it like I did at first
% (at the top of this file where you extract and imshow a frame at a
time.)
msgbox('Done this experiment!');
catch ME
% Some error happened if you get here.
strErrorMessage = sprintf('Error extracting movie frames
from:\n\n%s\n\nError: %s\n\n)', movieFullFileName, ME.message);
uiwait(msgbox(strErrorMessage));
end

MATLAB adding slider on a figure

I have a 576x576x150 matrix. Each 576x576 set represents an image. When I want to plot one frame I do it by using the plot command:
figure(1);
imshow(B(:,:,45),[]) % plots frame 45
title('45') % tells frame number
However I would like to add a slider to the plot, so I can move from 1-150 frame within the figure.I've seen examples of people using uicontrol but I don't know how to code it. In addition to that, I would like to have a title on top of the figure telling me the frame number.
Here is how I do it. I like to keep a single function that does the plotting so you don't recycle commands elsewhere. You could replace the first two lines by function test(B) to use you own B matrix. This code is pretty easy to extend. You will also want to play with the layout to suit your purpose.
function test
B=rand(576,576,150);
fig=figure(100);
set(fig,'Name','Image','Toolbar','figure',...
'NumberTitle','off')
% Create an axes to plot in
axes('Position',[.15 .05 .7 .9]);
% sliders for epsilon and lambda
slider1_handle=uicontrol(fig,'Style','slider','Max',150,'Min',1,...
'Value',2,'SliderStep',[1/(150-1) 10/(150-1)],...
'Units','normalized','Position',[.02 .02 .14 .05]);
uicontrol(fig,'Style','text','Units','normalized','Position',[.02 .07 .14 .04],...
'String','Choose frame');
% Set up callbacks
vars=struct('slider1_handle',slider1_handle,'B',B);
set(slider1_handle,'Callback',{#slider1_callback,vars});
plotterfcn(vars)
% End of main file
% Callback subfunctions to support UI actions
function slider1_callback(~,~,vars)
% Run slider1 which controls value of epsilon
plotterfcn(vars)
function plotterfcn(vars)
% Plots the image
imshow(vars.B(:,:,get(vars.slider1_handle,'Value')));
title(num2str(get(vars.slider1_handle,'Value')));
The idea is to use uicontrol() to enable sliding/scrolling.
The following code is for scrolling (created by Evan Brooks, you can modify it to sliding):
function scrollfigdemo
% create new figure window
f = figure;
set(f,'doublebuffer', 'on', 'resize', 'off')
% set columns of plots
cols = 2;
% create 5 data sets to plot
x=0:1e-2:2*pi;
y{1}=sin(x);
y{2}=cos(x);
y{3}=tan(x);
y{4}=x.^2;
y{5}=x.^3;
% determine required rows of plots
rows = ceil(length(y)/cols);
% increase figure width for additional axes
fpos = get(gcf, 'position');
scrnsz = get(0, 'screensize');
fwidth = min([fpos(3)*cols, scrnsz(3)-20]);
fheight = fwidth/cols*.75; % maintain aspect ratio
set(gcf, 'position', [10 fpos(2) fwidth fheight])
% setup all axes
buf = .15/cols; % buffer between axes & between left edge of figure and axes
awidth = (1-buf*cols-.08/cols)/cols; % width of all axes
aidx = 1;
rowidx = 0;
while aidx <= length(y)
for i = 0:cols-1
if aidx+i <= length(y)
start = buf + buf*i + awidth*i;
apos{aidx+i} = [start 1-rowidx-.92 awidth .85];
a{aidx+i} = axes('position', apos{aidx+i});
end
end
rowidx = rowidx + 1; % increment row
aidx = aidx + cols; % increment index of axes
end
% make plots
axes(a{1}), plot(x,y{1}), title('sine'), xlabel('x'), ylabel('sin(x)')
axes(a{2}), plot(x,y{2}), title('cosine'), xlabel('x'), ylabel('cos(x)')
axes(a{3}), plot(x,y{3}), title('tangent'), xlabel('x'), ylabel('tan(x)')
axes(a{4}), plot(x,y{4}), title('x^2'), xlabel('x'), ylabel('x^2')
axes(a{5}), plot(x,y{5}), title('x^3'), xlabel('x'), ylabel('x^3')
% determine the position of the scrollbar & its limits
swidth = max([.03/cols, 16/scrnsz(3)]);
ypos = [1-swidth 0 swidth 1];
ymax = 0;
ymin = -1*(rows-1);
% build the callback that will be executed on scrolling
clbk = '';
for i = 1:length(a)
line = ['set(',num2str(a{i},'%.13f'),',''position'',[', ...
num2str(apos{i}(1)),' ',num2str(apos{i}(2)),'-get(gcbo,''value'') ', num2str(apos{i}(3)), ...
' ', num2str(apos{i}(4)),'])'];
if i ~= length(a)
line = [line,','];
end
clbk = [clbk,line];
end
% create the slider
uicontrol('style','slider', ...
'units','normalized','position',ypos, ...
'callback',clbk,'min',ymin,'max',ymax,'value',0);

How to find the index from a large scatter plot in matlab?

I have a scatter plot with about 6000 items.
x = rand(1,6000);
y = rand(1,6000);
scatter(x,y)
Is there a way to find the index of a given point using the GUI? (We zoom into data, and want to find the specific index that gave rise to a point)
Here's a very simple solution:
Open a plot > data cursor > edit text update function
Set the text update function to:
function output_txt = myFunction(obj,event_obj)
% Display the position of the data cursor
% obj Currently not used (empty)
% event_obj Handle to event object
% output_txt Data cursor text string (string or cell array of strings).
pos = get(event_obj,'Position');
% Import x and y
x = get(get(event_obj,'Target'),'XData');
y = get(get(event_obj,'Target'),'YData');
% Find index
index_x = find(x == pos(1));
index_y = find(y == pos(2));
index = intersect(index_x,index_y);
% Set output text
output_txt = {['X: ',num2str(pos(1),4)], ...
['Y: ',num2str(pos(2),4)], ...
['Index: ', num2str(index)]};
% If there is a Z-coordinate in the position, display it as well
if length(pos) > 2
output_txt{end+1} = ['Z: ',num2str(pos(3),4)];
end
Results:
Just FYI, if you want to do this programatically, then here's a good article on it here.
You can use the X, Y position to search for the point:
%export the cursor to the workspace
possibleXpositions = find(x == cursor_info.Position(1));
possibleYPositions = find(y == cursor_info.Position(2));
position = intersect(possibleXpositions, possibleYPositions);
position will hold the index of your selected random number.
As a one liner:
position = intersect(find(x == cursor_info.Position(1)), find(y == cursor_info.Position(2)));

Extracting image region within boundary

I have to do a project using 2D CT images and segment liver and tumor in it using Matlab(only). Initially i have to segment liver region alone. I use region growing for liver segmentation. It gets seed point as input.
The output is an image with a boundary for liver region. Now I need the region that is surrounded by the boundary alone.
My program has a main program and a regionGrowing.m function. As I'm a new user am not allowed to post images. If you do need images I will mail you. Kindly help me.
% mainreg.m
IR=imread('nfliver5.jpg');
figure, imshow(IR), hold all
poly = regionGrowing(IR,[],15,1200); % click somewhere inside the liver
plot(poly(:,1), poly(:,2), 'LineWidth', 2, 'Color', [1 1 1])
%regionGrowing.m
function [P, J] = regionGrowing(cIM, initPos, thresVal, maxDist, tfMean, tfFillHoles, tfSimplify)
% REGIONGROWING Region growing algorithm for 2D/3D grayscale images
%
% Syntax:
% P = regionGrowing();
% P = regionGrowing(cIM);
% P = regionGrowing(cIM, initPos)
% P = regionGrowing(..., thresVal, maxDist, tfMean, tfFillHoles, tfSimpl)
% [P, J] = regionGrowing(...);
%
% Inputs:
% cIM: 2D/3D grayscale matrix {current image}
% initPos: Coordinates for initial seed position {ginput position}
% thresVal: Absolute threshold level to be included {5% of max-min}
% maxDist: Maximum distance to the initial position in [px] {Inf}
% tfMean: Updates the initial value to the region mean (slow) {false}
% tfFillHoles: Fills enclosed holes in the binary mask {true}
% tfSimplify: Reduces the number of vertices {true, if dpsimplify exists}
%
% Outputs:
% P: VxN array (with V number of vertices, N number of dimensions)
% P is the enclosing polygon for all associated pixel/voxel
% J: Binary mask (with the same size as the input image) indicating
% 1 (true) for associated pixel/voxel and 0 (false) for outside
%
% Examples:
% % 2D Example
% load example
% figure, imshow(cIM, [0 1500]), hold all
% poly = regionGrowing(cIM, [], 300); % click somewhere inside the lungs
% plot(poly(:,1), poly(:,2), 'LineWidth', 2)
%
% % 3D Example
% load mri
% poly = regionGrowing(squeeze(D), [66,55,13], 60, Inf, [], true, false);
% plot3(poly(:,1), poly(:,2), poly(:,3), 'x', 'LineWidth', 2)
%
% Requirements:
% TheMathWorks Image Processing Toolbox for bwboundaries() and axes2pix()
% Optional: Line Simplification by Wolfgang Schwanghart to reduce the
% number of polygon vertices (see the MATLAB FileExchange)
%
% Remarks:
% The queue is not preallocated and the region mean computation is slow.
% I haven't implemented a preallocation nor a queue counter yet for the
% sake of clarity, however this would be of course more efficient.
%
% Author:
% Daniel Kellner, 2011, braggpeaks{}googlemail.com
% History: v1.00: 2011/08/14
% error checking on input arguments
if nargin > 7
error('Wrong number of input arguments!')
end
if ~exist('cIM', 'var')
himage = findobj('Type', 'image');
if isempty(himage) || length(himage) > 1
error('Please define one of the current images!')
end
cIM = get(himage, 'CData');
end
if ~exist('initPos', 'var') || isempty(initPos)
himage = findobj('Type', 'image');
if isempty(himage)
himage = imshow(cIM, []);
end
% graphical user input for the initial position
p = ginput(1);
% get the pixel position concerning to the current axes coordinates
initPos(1) = round(axes2pix(size(cIM, 2), get(himage, 'XData'), p(2)));
initPos(2) = round(axes2pix(size(cIM, 1), get(himage, 'YData'), p(1)));
end
if ~exist('thresVal', 'var') || isempty(thresVal)
thresVal = double((max(cIM(:)) - min(cIM(:)))) * 0.05;
end
if ~exist('maxDist', 'var') || isempty(maxDist)
maxDist = Inf;
end
if ~exist('tfMean', 'var') || isempty(tfMean)
tfMean = false;
end
if ~exist('tfFillHoles', 'var')
tfFillHoles = true;
end
if isequal(ndims(cIM), 2)
initPos(3) = 1;
elseif isequal(ndims(cIM),1) || ndims(cIM) > 3
error('There are only 2D images and 3D image sets allowed!')
end
[nRow, nCol, nSli] = size(cIM);
if initPos(1) < 1 || initPos(2) < 1 ||...
initPos(1) > nRow || initPos(2) > nCol
error('Initial position out of bounds, please try again!')
end
if thresVal < 0 || maxDist < 0
error('Threshold and maximum distance values must be positive!')
end
if ~isempty(which('dpsimplify.m'))
if ~exist('tfSimplify', 'var')
tfSimplify = true;
end
simplifyTolerance = 1;
else
tfSimplify = false;
end
% initial pixel value
regVal = double(cIM(initPos(1), initPos(2), initPos(3)));
% text output with initial parameters
disp(['RegionGrowing Opening: Initial position (' num2str(initPos(1))...
'|' num2str(initPos(2)) '|' num2str(initPos(3)) ') with '...
num2str(regVal) ' as initial pixel value!'])
% preallocate array
J = false(nRow, nCol, nSli);
% add the initial pixel to the queue
queue = [initPos(1), initPos(2), initPos(3)];
%%% START OF REGION GROWING ALGORITHM
while size(queue, 1)
% the first queue position determines the new values
xv = queue(1,1);
yv = queue(1,2);
zv = queue(1,3);
% .. and delete the first queue position
queue(1,:) = [];
% check the neighbors for the current position
for i = -1:1
for j = -1:1
for k = -1:1
if xv+i > 0 && xv+i <= nRow &&... % within the x-bounds?
yv+j > 0 && yv+j <= nCol &&... % within the y-bounds?
zv+k > 0 && zv+k <= nSli &&... % within the z-bounds?
any([i, j, k]) &&... % i/j/k of (0/0/0) is redundant!
~J(xv+i, yv+j, zv+k) &&... % pixelposition already set?
sqrt( (xv+i-initPos(1))^2 +...
(yv+j-initPos(2))^2 +...
(zv+k-initPos(3))^2 ) < maxDist &&... % within distance?
cIM(xv+i, yv+j, zv+k) <= (regVal + thresVal) &&...% within range
cIM(xv+i, yv+j, zv+k) >= (regVal - thresVal) % of the threshold?
% current pixel is true, if all properties are fullfilled
J(xv+i, yv+j, zv+k) = true;
% add the current pixel to the computation queue (recursive)
queue(end+1,:) = [xv+i, yv+j, zv+k];
if tfMean
regVal = mean(mean(cIM(J > 0))); % --> slow!
end
end
end
end
end
end
%%% END OF REGION GROWING ALGORITHM
% loop through each slice, fill holes and extract the polygon vertices
P = [];
for cSli = 1:nSli
if ~any(J(:,:,cSli))
continue
end
% use bwboundaries() to extract the enclosing polygon
if tfFillHoles
% fill the holes inside the mask
J(:,:,cSli) = imfill(J(:,:,cSli), 'holes');
B = bwboundaries(J(:,:,cSli), 8, 'noholes');
else
B = bwboundaries(J(:,:,cSli));
end
newVertices = [B{1}(:,2), B{1}(:,1)];
% simplify the polygon via Line Simplification
if tfSimplify
newVertices = dpsimplify(newVertices, simplifyTolerance);
end
% number of new vertices to be added
nNew = size(newVertices, 1);
% append the new vertices to the existing polygon matrix
if isequal(nSli, 1) % 2D
P(end+1:end+nNew, :) = newVertices;
else % 3D
P(end+1:end+nNew, :) = [newVertices, repmat(cSli, nNew, 1)];
end
end
% text output with final number of vertices
disp(['RegionGrowing Ending: Found ' num2str(length(find(J)))...
' pixels within the threshold range (' num2str(size(P, 1))...
' polygon vertices)!'])
If I understand you correctly, you have a binary image of the boundary of the kidney and now need to set the inside of the boundary to 1s. To do this, you can use the imfill() function with the 'holes' setting on.
BW2 = imfill(BW,'holes');
EDIT: Looking at the code, it seems that it does what you want already.
% Outputs:
% J: Binary mask (with the same size as the input image) indicating
% 1 (true) for associated pixel/voxel and 0 (false) for outside
so you just need to get the second output as well:
IR=imread('nfliver5.jpg');
figure, imshow(IR), hold all
[poly im] = regionGrowing(IR,[],15,1200); % click somewhere inside the liver
imshow(im,[])
Now im is a binary image with your segmented region.
EDIT2:
Once you have the binary image im, you can simply use element-wise multiplication to remove all parts of the orignal image outside the segmented region.
SEG = IR.*im;
imshow(SEG,[])
EDIT3:
For 3D images, you need to specify the coordinates manually, and not by using the mouse. This is because the mouse only gives us 2 coordinates (x and y) and you need 3 (x,y and z). So just find the coordinates you need by looking at the image, and then choosing an appropriate z coordinate.
%Example coordinates,
coordinates = [100 100 5]
poly = regionGrowing(squeeze(IR), coordinates, 60, Inf, [], true, false);