Clear Filters
Clear Filters

How to create a Binary image from two columns of raw data

9 views (last 30 days)
Hello, I have the following dataset, which consists of two columns. I have also attached a scatter plot of the dataset, where first column is on x axis and 2nd column is on y axis.
I want to create a Binary image for the dataset.
How can i do it in MATLAB

Answers (3)

DGM on 2 Nov 2022
This is similar to the prior answer, but in this case, we need to deal with scaling both x and y data.
load matlab.mat
outsize = [500 500];
% rescale data to fit width, generate indices
dlen = size(pdw,1);
x0 = pdw(:,1);
y0 = pdw(:,2);
x0 = (outsize(2)-1)*normalize(x0,'range') + 1;
xidx = 1:outsize(2);
yidx = interp1(x0,y0,xidx);
yidx = outsize(1) - (outsize(1)-1)*normalize(yidx,'range');
% display a dummy image to fix geometry
% create ROI object and configure
ROI = images.roi.Polyline(gca);
ROI.Position = [xidx(:) yidx(:)];
% convert to logical mask
outpict = createMask(ROI);
Note that strokes are drawn across any periods where there are no samples being taken.
The same configuration of xidx,yidx would work with the rudimentary non-aa polyline example given in that same thread.
Med Future
Med Future on 8 Nov 2022
@DGM Did we able to find values from image as on original dataset?
DGM on 9 Nov 2022
If you knew what the original range of y had been, you might recover the y-data with a resolution determined by the height of the image. All the actual x-data will be lost. It's merely one dot per sample. Any jumps in x are not represented by the image.
Of course, I don't know why you would be wanting to recover the data from the image. Even if the issue with the nonuniform x-data weren't the case, you'd still be losing information in converting it to a raster image.
% you have an output image
inpict = imread('superwidepict.png');
% and a limited-precision stored reference to the original data range
y0range = [1.41351e-05 0.00327854];
% you can recover the y-position of each dot
[yidx,~] = find(inpict);
% you can rescale to data units
yrec = y0range(2) - rescale(yidx,0,range(y0range));
% compare to the original data
load matlab.mat
y0 = pdw(:,2);
% compare original and recovered data
xl = [1830 3196]; % look at a closeup
yl = [0.0061 0.2693]*1E-3;
plot(y0); xlim(xl); ylim(yl)
plot(yrec); xlim(xl); ylim(yl)
% plot the error

Sign in to comment.

Image Analyst
Image Analyst on 2 Nov 2022
What do you want the size of this image to be in pixels? How many rows and columns?
s = load('matlab1.mat')
xy = s.pdw;
x = xy(:, 1);
y = xy(:, 2);
subplot(2, 1, 1);
plot(x, y, 'b.', 'MarkerSize', 10);
grid on;
% Define the size of the image you want
rows = 512;
columns = 1500;
% Rescale data
x = rescale(x, 1, columns);
y = rescale(y, 1, rows);
binaryImage = false(rows, columns);
for k = 1 : length(x)
row = rows - round(y(k)) + 1;
col = round(x(k));
binaryImage(row, col) = true;
subplot(2, 1, 2);
DGM on 3 Nov 2022
The comment I posted on my answer above generates 14 images, each 1000px wide, rendering 1px per datapoint (i.e. not a polyline)
Image Analyst
Image Analyst on 9 Nov 2022
Let's step back and ask WHY you want 1000 binary images, or even one binary image from your data? I see no need for it, and you haven't given any reason - you just said that you want that but with no justification. What do the original coordinates represent in reality?

Sign in to comment.

Walter Roberson
Walter Roberson on 2 Nov 2022
filename = 'matlab.mat';
datastruct = load(filename, 'pdw');
pdw = datastruct.pdw;
targetsize = [930 1860]; %rows, columns
margin = 5;
scaled_x = rescale(pdw(:,1), margin+1, targetsize(2)-margin);
scaled_y = rescale(pdw(:,2), margin+1, targetsize(1)-margin);
canvas = zeros(targetsize(1), targetsize(2), 3, 'uint8');
r = 3;
xyr = [scaled_x, scaled_y, r * ones(size(scaled_x))];
canvas = insertShape(canvas, 'circle', xyr, 'Color','white');
binary = canvas(:,:,1) > 0;
Except for the imshow() at the end, none of this requires the graphics system or creating any files.
DGM on 2 Nov 2022
Edited: DGM on 2 Nov 2022
FWIW, it does require CVT.
Not that I'm in any position to object, since I got lazy and used IPT ROI tools. Still, the linked comment has a polyline implementation that does not. I suppose even imshow() is an IPT dependency depending on version.
I suppose I could've simplified the rescaling though.
Walter Roberson
Walter Roberson on 2 Nov 2022
(CVT means Computer Vision Toolbox in this context, and IPT means Image Processing Toolbox)

Sign in to comment.


Find more on Convert Image Type in Help Center and File Exchange




Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!