MATLAB: Fitting envelope peak points

fittingflipped textMATLABpeaksupside down text on gui

I am facing some problems trying to create a fitting curve that will pass through maximum peaks. I tried findpeaks

findpeaks(Sig)
hold all
plot(Sig,'k')

as well as envelope

[up, lo] = envelope(Sig,'peak');
plot(Sig, 'o-k');
hold on
plot(up,'r');
plot(lo,'b');
legend ('bb','up','down')
grid

How can i create a fitting curve which will pass through max peak points? Will a solution be to export peaks into a new array, plot them and then create a fitting curve or there is another way?

Thanks in advance!

Best Answer

Just try interp1() or spline(). Pass in your peak points and then the x values of the whole array, something like

[peakValues, indexes] = findpeaks(Sig);
yOut = spline(indexes, peakValues, 1:length(Sig));
plot(yOut, 'b-', 'LineWidth', 2);
grid on;

Let me know if it works. Attach your Sig data if it doesn't. Accept this answer if it does.

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MATLAB: How to separate a 3D shape with repetitions to each repetition

Try this:

clc;    % Clear the command window.
clearvars;
close all;  % Close all figures (except those of imtool.)
workspace;  % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 20;
s = load('matrix.mat')
FE = s.FE
x = FE(1, :);
y = FE(2, :);
z = FE(3, :);
subplot(2, 2, 1);
plot3(x, y, z, 'b.');
xlabel('X', 'FontSize', fontSize);
ylabel('Y', 'FontSize', fontSize);
zlabel('Z', 'FontSize', fontSize);
grid on;
title('Original Single Curve', 'FontSize', fontSize);
numPoints = length(x)
% Find distances from starting point.
distances = sqrt((x - x(1)).^ 2 + (y - y(1)).^ 2 +(z - z(1)).^ 2);
subplot(2, 2, 2);
plot(distances);
xlabel('Index', 'FontSize', fontSize);
ylabel('Distance from point 1', 'FontSize', fontSize);
% Find valleys by finding peaks of inverted signal.
[peakValues, indexesOfPeaks] = findpeaks(-distances);
peakValues = -peakValues; % Invert again.
% Add on very first and very last points
indexesOfPeaks = [1, indexesOfPeaks, numPoints];
peakValues = [distances(1), peakValues, distances(end)];
hold on;
plot(indexesOfPeaks, peakValues, 'rv');
grid on;
title('Distances from point #1', 'FontSize', fontSize);
% Extract out each part of the curve
subplot(2, 2, 3:4);
curveCount = 0;
for k = 1 : 2 : length(indexesOfPeaks) - 1
  index1 = indexesOfPeaks(k);
  index2 = indexesOfPeaks(k + 2) - 1;
  fprintf('Extracting points %d to %d.\n', index1, index2);
  xSingles{k} = x(index1:index2);
  ySingles{k} = y(index1:index2);
  zSingles{k} = z(index1:index2);
  plot3(xSingles{k}, ySingles{k}, zSingles{k}, '-', 'LineWidth', 2);
  hold on;
  curveCount = curveCount + 1;
end
xlabel('X', 'FontSize', fontSize);
ylabel('Y', 'FontSize', fontSize);
zlabel('Z', 'FontSize', fontSize);
caption = sprintf('%d curves', curveCount);
title(caption, 'FontSize', 20);
grid on;

MATLAB: Fit a polynimial function on a image curve

How about this:

% Demo to find fitted curve.
% By Image Analyst
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 = 22;
%--------------------------------------------------------------------------------------------------------


%    READ IN IMAGE
folder = pwd;
baseFileName = 'image.jpeg';
% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);
% Check if file exists.
if ~exist(fullFileName, 'file')
	% The file doesn't exist -- didn't find it there in that folder.
	% Check the entire search path (other folders) for the file by stripping off the folder.
	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.
% numberOfColorChannels should be = 1 for a gray scale image, and 3 for an RGB color image.
[rows, columns, numberOfColorChannels] = size(grayImage);
if numberOfColorChannels > 1
	% It's not really gray scale like we expected - it's color.
	% Use weighted sum of ALL channels to create a gray scale image.
	grayImage = rgb2gray(grayImage);
	% ALTERNATE METHOD: Convert it to gray scale by taking only the green channel,
	% which in a typical snapshot will be the least noisy channel.
	% grayImage = grayImage(:, :, 2); % Take green channel.
end
%--------------------------------------------------------------------------------------------------------
%    SEGMENTATION OF IMAGE
% Get a binary image
binaryImage = imbinarize(grayImage);
subplot(3, 1, 1);
imshow(binaryImage, []);
impixelinfo;
title('Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');
hFig = gcf;
hFig.WindowState = 'maximized'; % May not work in earlier versions of MATLAB.
drawnow;
%--------------------------------------------------------------------------------------------------------
% REMOVE BOTTOM ARC
for col = 1 : columns
	thisCol = binaryImage(:, col);
	% Remove largest blob.
	biggestBlob = bwareafilt(thisCol, 1);
	thisCol(biggestBlob) = false;
	binaryImage(:, col) = thisCol;
end
% Display it.

subplot(3, 1, 2);
imshow(binaryImage)
grid on;
title('Without bottom arc', 'FontSize', fontSize, 'Interpreter', 'None');
% Get (x,y) of what's left
[y, x] = find(binaryImage);
% Add a tiny bit of noise because sometimes there are multiple y for the same x.
x = x + 0.001 * rand(1, length(x));
% Sort them
[x, sortOrder] = sort(x, 'ascend');
y = y(sortOrder);
% Filter with movmean
ySmoothed = movmean(y, 5);
% Display it.
subplot(3, 1, 3);
imshow(binaryImage)
grid on;
title('With Fitted Curve in Red', 'FontSize', fontSize, 'Interpreter', 'None');
hold on
plot(x, ySmoothed, 'r-', 'LineWidth', 3);

Best Answer

Related Solutions

MATLAB: How to separate a 3D shape with repetitions to each repetition

MATLAB: Fit a polynimial function on a image curve

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