remove backgroung from the image

Can you help me to remove the backgrond from the image?

this is example of image

Answer 1

[Image Analyst]

Try the Color Thresholder. Use HSV color space and adjust the S slider. Or the V slider. Then tell it to export the code.

[Frisda Sianipar]

This code is for image segmentation from removing background - green channel - clahe - canny. But in this code we still input images one by one And I want the code to immediately read all the images in one folder and save the output in another folder. Can you help me? Please, thankyou in advance

clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
workspace;  % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 16;

%===============================================================================
% Get the name of the image the user wants to use.
baseFileName = 'image.jpg';
folder = pwd;
fullFileNam
e = 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

%=======================================================================================
% Read in demo image.
rgbImage = imread(fullFileName);
% Get the dimensions of the image.
% [rows, columns, numberOfColorChannels] = size(rgbImage)

% Display image.
figure(1);
imshow(rgbImage, []);
impixelinfo;
axis on;
caption = sprintf('Original Color Image\n%s', baseFileName);
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.

% Set up figure properties:
% Enlarge figure to full screen.
% set(gcf, 'Units', 'Normalized', 'OuterPosition', [0 0.05 1 0.95]);
% Get rid of tool bar and pulldown menus that are along top of figure.
% set(gcf, 'Toolbar', 'none', 'Menu', 'none');
% Give a name to the title bar.
% set(gcf, 'Name', 'Demo by ImageAnalyst', 'NumberTitle', 'Off')
% drawnow;

[mask, maskedRGBImage] = createMask(rgbImage);
% Extract the largest blob only.  That will be the hand.
mask = bwareafilt(mask, 1);



% Mask the image using bsxfun() function to multiply the mask by each channel individually.
maskedRgbImage = bsxfun(@times, rgbImage, cast(mask, 'like', rgbImage));

% Display the image.
figure(2);
imshow(maskedRgbImage, []);
% impixelinfo;
% title('Masked Image', 'FontSize', fontSize, 'Interpreter', 'None');
axis on;
drawnow;
%green channel
 green_channel = maskedRgbImage(:,:,2);
 figure(3),imshow(green_channel) 
 %CLAHE
CLAHE = adapthisteq(green_channel);
figure, fig4=imshow(CLAHE);
%Canny
ER = edge(CLAHE, 'canny');
EG = edge(CLAHE, 'canny');
EB = edge(CLAHE, 'canny');
anyedge = ER | EG | EB;
figure,fig5=imshow(anyedge);

% [n, r] = fboxcount(anyedge,'slope');
% df = -diff(log(n))./diff(log(r));
% %Menampilkan hasil dimensi
% disp(['Df= ' num2str(mean(df(4:8)))]);


function [BW,maskedRGBImage] = createMask(RGB)
%createMask  Threshold RGB image using auto-generated code from colorThresholder app.
%  [BW,MASKEDRGBIMAGE] = createMask(RGB) thresholds image RGB using
%  auto-generated code from the colorThresholder app. The colorspace and
%  range for each channel of the colorspace were set within the app. The
%  segmentation mask is returned in BW, and a composite of the mask and
%  original RGB images is returned in maskedRGBImage.

% Auto-generated by colorThresholder app on 11-Aug-2018
%------------------------------------------------------


% Convert RGB image to chosen color space
I = rgb2hsv(RGB);

% Define thresholds for channel 1 based on histogram settings
channel1Min = 0.000;
channel1Max = 1.000;

% Define thresholds for channel 2 based on histogram settings
channel2Min = 0.215;
channel2Max = 1.000;

% Define thresholds for channel 3 based on histogram settings
channel3Min = 0.082;
channel3Max = 0.810;

% Create mask based on chosen histogram thresholds
sliderBW = (I(:,:,1) >= channel1Min ) & (I(:,:,1) <= channel1Max) & ...
	(I(:,:,2) >= channel2Min ) & (I(:,:,2) <= channel2Max) & ...
	(I(:,:,3) >= channel3Min ) & (I(:,:,3) <= channel3Max);
BW = sliderBW;

% Initialize output masked image based on input image.
maskedRGBImage = RGB;

% Set background pixels where BW is false to zero.
maskedRGBImage(repmat(~BW,[1 1 3])) = 0;

end

[Image Analyst]

Code samples are in the FAQ:

https://matlab.fandom.com/wiki/FAQ#How_can_I_process_a_sequence_of_files.3F

[Frisda Sianipar]

Thank you sir, i will try

[Frisda Sianipar]

But sir i want to save all the output automatic

[Image Analyst]

What's not automatic about it? Once you've defined the thresholds, you can apply it to image after image automatically with no further user involvement needed.

[Frisda Sianipar]

save the output of segmentation sir

[Walter Roberson]

You can use sprintf() or compose() to generate filenames, and call save() passing in the file name and the name of the variable to save.