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I am trying to outline all peaks in an image. The brightest lines are the peaks. I am using Matlab. This is what I have so far....
Any help will be greatly appreciated. Here is the image.
a = imread('duneLiDARs.png');
%b = imregionalmax(a);
%a = rgb2gray(a);
c = edge(a,'Sobel');
b = edge(a,'log',.0006);
d = edge(a,'log');
c= imfuse(a,d);
d= d-b;
subplot(2,2,1), imshow(a)
subplot(2,2,2), imshow(b)
subplot(2,2,3), imshow(c)
subplot(2,2,4), imshow(d)
%imshow(b);
%c = imadd(a,b);
%imshow(b);
you need to define what do you consider as peaks - what is the desired output for your image.
however, there are some general 2D peaks finding function, the following code uses FEX's extrema2:
% load image and remove extreme noise
im = medfilt2( im2double(imread('dune.png')));
% find peaks using extrema2
[XMAX,IMAX,XMIN,IMIN] = extrema2(im);
% eliminate peaks under minimum threshold
underThresh = XMAX < 0.15;
IMAX(underThresh) = [];
XMAX(underThresh) = [];
% plotting
subplot(121);
surf(im,'EdgeColor','none');
hold on;
[y,x] = ind2sub(size(im),IMAX);
scatter3(x,y,XMAX,'r','filled');
axis square
subplot(122);
imshow(im,[]);
hold on;
scatter(x,y,'r','filled');
i have to extract each characters from a image here i am uploading the code it is segmenting the horizontal lines but not able to segment the each characters along with the horizontal line segmentation loop. some1 please help to correct the code
this is the previous code:
%%horizontal histogram
H = sum(rotatedImage, 2);
darkPixels = H < 100; % Threshold
% label
[labeledRegions, numberOfRegions] = bwlabel(darkPixels);
fprintf('Number of regions = %d\n', numberOfRegions);
% Find centroids
measurements = regionprops(labeledRegions, 'Centroid');
% Get them into an array
allCentroids = [measurements.Centroid];
xCentroids = int32(allCentroids(1:2:end));
yCentroids = int32(allCentroids(2:2:end));
% Now you can just crop out some line of text you're interested in, into a separate image:
hold off;
plotLocation = 8;
for band = 1 : numberOfRegions-1
row1 = yCentroids(band);
row2 = yCentroids(band+1);
thisLine = rotatedImage(row1 : row2, :);
subplot(7, 2, plotLocation)
imshow(thisLine, [])
%% Let's compute and display the histogram.
verticalProjection = sum(thisLine, 2);
set(gcf, 'NumberTitle', 'Off')
t = verticalProjection;
t(t==0) = inf;
mayukh=min(t);
% 0 where there is background, 1 where there are letters
letterLocations = verticalProjection > mayukh;
% Find Rising and falling edges
d = diff(letterLocations);
startingRows = find(d>0);
endingRows = find(d<0);
% Extract each region
y=1;
for k = 1 : length(startingRows)
% Get sub image of just one character...
subImage = thisLine(:, startingRows(k):endingRows(k));
[L,num] = bwlabel(subImage);
for z= 1 : num
bw= ismember( L, z);
% Construct filename for this particular image.
baseFileName = sprintf('templates %d.png', y);
y=y+1;
% Prepend the folder to make the full file name.
fullFileName = fullfile('C:\Users\Omm\Downloads\', baseFileName);
% Do the write to disk.
imwrite(bw, fullFileName);
pause(2);
imshow(bw);
pause(5)
end;
y=y+2;
end;
plotLocation = plotLocation + 2;
end
but not segmenting the whole lines
Why don't you simply use regionprops with 'Image' property?
img = imread('http://i.stack.imgur.com/zpYa5.png'); %// read the image
bw = img(:,:,1) > 128; %// conver to mask
Use some minor morphological operations to handle spurious pixels
dbw = imdilate(bw, ones(3));
lb = bwlabel(dbw).*bw; %// label each character as a connected component
Now you can use regionprops to get each image
st = regionprops( lb, 'Image' );
Visualize the results
figure;
for ii=1:numel(st),
subplot(4,5,ii);
imshow(st(ii).Image,'border','tight');
title(num2str(ii));
end
I want to convert this answer's code to imshow.
It creates a movie in MOVIE2AVI by
%# preallocate
nFrames = 20;
mov(1:nFrames) = struct('cdata',[], 'colormap',[]);
%# create movie
for k=1:nFrames
surf(sin(2*pi*k/20)*Z, Z)
mov(k) = getframe(gca);
end
close(gcf)
movie2avi(mov, 'myPeaks1.avi', 'compression','None', 'fps',10);
My pseudocode
%# preallocate
nFrames = 20;
mov(1:nFrames) = struct('cdata',[], 'colormap',[]);
%# create movie
for k=1:nFrames
imshow(signal(:,k,:),[1 1 1]) % or simply imshow(signal(:,k,:))
drawnow
mov(k) = getframe(gca);
end
close(gcf)
movie2avi(mov, 'myPeaks1.avi', 'compression','None', 'fps',10);
However, this creates the animation in the screen, but it saves only a AVI -file which size is 0 kB. The file myPeaks1.avi is stored properly after running the surf command but not from imshow.
I am not sure about the command drawnow.
Actual case code
%% HSV 3rd version
% https://stackoverflow.com/a/29801499/54964
rgbImage = imread('http://i.stack.imgur.com/cFOSp.png');
% Extract blue using HSV
hsvImage=rgb2hsv(rgbImage);
I=rgbImage;
R=I(:,:,1);
G=I(:,:,2);
B=I(:,:,3);
R((hsvImage(:,:,1)>(280/360))|(hsvImage(:,:,1)<(200/360)))=255;
G((hsvImage(:,:,1)>(280/360))|(hsvImage(:,:,1)<(200/360)))=255;
B((hsvImage(:,:,1)>(280/360))|(hsvImage(:,:,1)<(200/360)))=255;
I2= cat(3, R, G, B);
% Binarize image, getting all the pixels that are "blue"
bw=im2bw(rgb2gray(I2),0.9999);
% The label most repeated will be the signal.
% So we find it and separate the background from the signal using label.
% Label each "blob"
lbl=bwlabel(~bw);
% Find the blob with the highes amount of data. That will be your signal.
r=histc(lbl(:),1:max(lbl(:)));
[~,idxmax]=max(r);
% Profit!
signal=rgbImage;
signal(repmat((lbl~=idxmax),[1 1 3]))=255;
background=rgbImage;
background(repmat((lbl==idxmax),[1 1 3]))=255;
%% Error Testing
comp_image = rgb2gray(abs(double(rgbImage) - double(signal)));
if ( sum(sum(comp_image(32:438, 96:517))) > 0 )
break;
end
%% Video
% 5001 units so 13.90 (= 4.45 + 9.45) seconds.
% In RGB, original size 480x592.
% Resize to 480x491
signal = signal(:, 42:532, :);
% Show 7 seconds (298 units) at a time.
% imshow(signal(:, 1:298, :));
%% Video VideoWriter
% movie2avi deprecated in Matlab
% https://stackoverflow.com/a/11054155/54964
% https://stackoverflow.com/a/29952648/54964
%# figure
hFig = figure('Menubar','none', 'Color','white');
Z = peaks;
h = imshow(Z, [], 'InitialMagnification',1000, 'Border','tight');
colormap parula; axis tight manual off;
set(gca, 'nextplot','replacechildren', 'Visible','off');
% set(gcf,'Renderer','zbuffer'); % on some Windows
%# preallocate
N = 40; % 491;
vidObj = VideoWriter('myPeaks3.avi');
vidObj.Quality = 100;
vidObj.FrameRate = 10;
open(vidObj);
%# create movie
for k=1:N
set(h, 'CData', signal(:,k:k+40,:))
% drawnow
writeVideo(vidObj, getframe(gca));
end
%# save as AVI file
close(vidObj);
How can you substitute the drawing function by imshow or corresponding?
How can you store the animation correctly?
Here is some code to try:
%// plot
hFig = figure('Menubar','none', 'Color','white');
Z = peaks;
%h = surf(Z);
h = imshow(Z, [], 'InitialMagnification',1000, 'Border','tight');
colormap jet
axis tight manual off
%// preallocate movie structure
N = 40;
mov = struct('cdata',cell(1,N), 'colormap',cell(1,N));
%// aninmation
for k=1:N
%set(h, 'ZData',sin(2*pi*k/N)*Z)
set(h, 'CData',sin(2*pi*k/N)*Z)
drawnow
mov(k) = getframe(hFig);
end
close(hFig)
%// save AVI movie, and open video file
movie2avi(mov, 'file.avi', 'Compression','none', 'Fps',10);
winopen('file.avi')
Result (not really the video, just a GIF animation):
Depending on the codecs installed on your machine, you can apply video compression, e.g:
movie2avi(mov, 'file.avi', 'Compression','XVID', 'Quality',100, 'Fps',10);
(assuming you have the Xvid encoder installed).
EDIT:
Here is my implementation of the code you posted:
%%// extract blue ECG signal
%// retrieve picture: http://stackoverflow.com/q/29800089
imgRGB = imread('http://i.stack.imgur.com/cFOSp.png');
%// detect axis lines and labels
imgHSV = rgb2hsv(imgRGB);
BW = (imgHSV(:,:,3) < 1);
BW = imclose(imclose(BW, strel('line',40,0)), strel('line',10,90));
%// clear those masked pixels by setting them to background white color
imgRGB2 = imgRGB;
imgRGB2(repmat(BW,[1 1 3])) = 255;
%%// create sliding-window video
len = 40;
signal = imgRGB2(:,42:532,:);
figure('Menubar','none', 'NumberTitle','off', 'Color','k')
hImg = imshow(signal(:,1:1+len,:), ...
'InitialMagnification',100, 'Border','tight');
vid = VideoWriter('signal.avi');
vid.Quality = 100;
vid.FrameRate = 60;
open(vid);
N = size(signal,2);
for k=1:N-len
set(hImg, 'CData',signal(:,k:k+len,:))
writeVideo(vid, getframe());
end
close(vid);
The result look like this:
I have to binarize image so I have twice as many white pixels as black pixels.
Someone gave me answer:
binarized = im2bw(image, 0.28)
and I'm not sure how do this person know that level 0.28 gives twice as many white as black?
In this code, I had to use gamma correction, use imhist, binarize. My code:
close all;
clear all;
clc;
img = imread('cameraman.tif');
img = double(img)/255;
coeff = 0.6;
gamma = img.^coeff;
figure;
subplot(121); imshow(img); title('Oryginalny');
subplot(122); imshow(gamma); title('Po korekcji gamma');
equalized = histeq(gamma,32);
figure;
subplot(221); imshow(gamma); title('Po korekcji gamma');
subplot(222); imshow(equalized); title('Wyrównany');
subplot(223); imhist(gamma); title('Po korekcji gamma');
subplot(224); imhist(equalized); title('Wyrównany');
SE = strel('disk', 3);
eroded = imerode(equalized,SE);
opening = imdilate(eroded,SE);
figure;
subplot(121); imshow(equalized); title('Wyrównany');
subplot(122); imshow(opening); title('Otwarcie');
binarized = im2bw(opening, 0.28);
figure;
imshow(binarized); title('Po binaryzacji');
w = binarized == 1;
b = binarized == 0;
biale = sum(w(:));
czarne = sum(b(:));
I have a video when in some place the video rotated ... I don't know the angle and to what Direction it move. I tried to use:
function [ output_args ] = aaa( filename )
hVideoSrc = vision.VideoFileReader(filename, 'ImageColorSpace', 'Intensity');
imgA = step(hVideoSrc); % Read first frame into imgA
imgB = step(hVideoSrc); % Read second frame into imgB
figure; imshowpair(imgA, imgB, 'montage');
title(['Frame A', repmat(' ',[1 70]), 'Frame B']);
figure; imshowpair(imgA,imgB,'ColorChannels','red-cyan');
title('Color composite (frame A = red, frame B = cyan)');
ptThresh = 0.1;
pointsA = detectFASTFeatures(imgA, 'MinContrast', ptThresh);
pointsB = detectFASTFeatures(imgB, 'MinContrast', ptThresh);
% Display corners found in images A and B.
figure; imshow(imgA); hold on;
plot(pointsA);
title('Corners in A');
figure; imshow(imgB); hold on;
plot(pointsB);
title('Corners in B');
% Extract FREAK descriptors for the corners
[featuresA, pointsA] = extractFeatures(imgA, pointsA);
[featuresB, pointsB] = extractFeatures(imgB, pointsB);
indexPairs = matchFeatures(featuresA, featuresB);
pointsA = pointsA(indexPairs(:, 1), :);
pointsB = pointsB(indexPairs(:, 2), :);
figure; showMatchedFeatures(imgA, imgB, pointsA, pointsB);
legend('A', 'B');
[tform, pointsBm, pointsAm] = estimateGeometricTransform(...
pointsB, pointsA, 'affine');
imgBp = imwarp(imgB, tform, 'OutputView', imref2d(size(imgB)));
pointsBmp = transformPointsForward(tform, pointsBm.Location);
figure;
showMatchedFeatures(imgA, imgBp, pointsAm, pointsBmp);
legend('A', 'B');
% Extract scale and rotation part sub-matrix.
H = tform.T;
R = H(1:2,1:2);
% Compute theta from mean of two possible arctangents
theta = mean([atan2(R(2),R(1)) atan2(-R(3),R(4))]);
% Compute scale from mean of two stable mean calculations
scale = mean(R([1 4])/cos(theta));
% Translation remains the same:
translation = H(3, 1:2);
% Reconstitute new s-R-t transform:
HsRt = [[scale*[cos(theta) -sin(theta); sin(theta) cos(theta)]; ...
translation], [0 0 1]'];
tformsRT = affine2d(HsRt);
imgBold = imwarp(imgB, tform, 'OutputView', imref2d(size(imgB)));
imgBsRt = imwarp(imgB, tformsRT, 'OutputView', imref2d(size(imgB)));
figure(2), clf;
imshowpair(imgBold,imgBsRt,'ColorChannels','red-cyan'), axis image;
title('Color composite of affine and s-R-t transform outputs');
% Reset the video source to the beginning of the file.
reset(hVideoSrc);
hVPlayer = vision.VideoPlayer; % Create video viewer
% Process all frames in the video
movMean = step(hVideoSrc);
imgB = movMean;
imgBp = imgB;
correctedMean = imgBp;
ii = 2;
Hcumulative = eye(3);
while ~isDone(hVideoSrc) && ii < 10
% Read in new frame
imgA = imgB; % z^-1
imgAp = imgBp; % z^-1
imgB = step(hVideoSrc);
movMean = movMean + imgB;
% Estimate transform from frame A to frame B, and fit as an s-R-t
H = cvexEstStabilizationTform(imgA,imgB);
HsRt = cvexTformToSRT(H);
Hcumulative = HsRt * Hcumulative;
imgBp = imwarp(imgB,affine2d(Hcumulative),'OutputView',imref2d(size(imgB)));
% Display as color composite with last corrected frame
step(hVPlayer, imfuse(imgAp,imgBp,'ColorChannels','red-cyan'));
correctedMean = correctedMean + imgBp;
ii = ii+1;
end
correctedMean = correctedMean/(ii-2);
movMean = movMean/(ii-2);
% Here you call the release method on the objects to close any open files
% and release memory.
release(hVideoSrc);
release(hVPlayer);
figure; imshowpair(movMean, correctedMean, 'montage');
title(['Raw input mean', repmat(' ',[1 50]), 'Corrected sequence mean']);
end
Code from here
http://www.mathworks.com/help/vision/examples/video-stabilization-using-point-feature-matching.html,
but the MatLab doesn't recognize the function detectFASTFeatures
Someone can help me ?
Maybe someone have other function that find this points.
It seems to be a function in the computer vision toolbox that only comes with MATLAB r2014a:
http://www.mathworks.com/help/vision/ref/detectfastfeatures.html
If you have an older version of the MATLAB with Computer Vision System Toolbox, you can use the vision.CornerDetector object.