How to remove unwanted portion from background?

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Ostu's thresholding method is good and easy. For some images it clearly idetified the object in interest, but some other images it lefts some unwanted portion. When dealing with more 1000 images running in batch and applying ostu's method is not giving any good outputs. How can I improve this algorithms or any other idea where after applying ostu's methods we can remove unwanted portion and that will applicable for all images.

Answers (5)

Image Analyst
Image Analyst on 18 Oct 2021
It often does not work well for images that do not have a nice well separated bimodal histogram. The triangle method works well for skewed histograms, like with a log-normal shape. I'm attaching my implementation.
imbinarize() has an 'adaptive' option that might work well for you.
  7 Comments
Image Analyst
Image Analyst on 18 Aug 2022
@Zara Khan I don't know. I haven't done it. If none of the papers links I gave you uses that particular method (deep learning) and you don't want to use any of the successful methods that they developed, used and published, then you're on your own. I'm no further along than you are, and I don't plan on going into gesture research so don't wait on me.

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yanqi liu
yanqi liu on 26 Oct 2021
sir,may be upload some image samples to develop
  1 Comment
Zara Khan
Zara Khan on 26 Oct 2021
Uploaded few images . Please see in Image Analyst's reply section. Thanks.

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yanqi liu
yanqi liu on 27 Oct 2021
sir,please check the follow code to get some information
clc; clear all; close all
urls={'https://ww2.mathworks.cn/matlabcentral/answers/uploaded_files/779463/img16.png',...
'https://ww2.mathworks.cn/matlabcentral/answers/uploaded_files/779458/img6.png',...
'https://ww2.mathworks.cn/matlabcentral/answers/uploaded_files/779453/img4.png',...
'https://ww2.mathworks.cn/matlabcentral/answers/uploaded_files/779448/img2.png',...
'https://ww2.mathworks.cn/matlabcentral/answers/uploaded_files/779443/img1.png',...
'https://ww2.mathworks.cn/matlabcentral/answers/uploaded_files/779438/img1%20(2).png'};
for k = 1 : length(urls)
im = imread(urls{k});
if ndims(im) == 3
im = rgb2gray(im);
end
im2 = imadjust(im,stretchlim(im),[]);
bw = imbinarize(im2,'adaptive','ForegroundPolarity','dark','Sensitivity',0.85);
bw = bwareaopen(bw, 100);
bw = imopen(bw, strel('line', 9, 90));
bw = imclose(bw, strel('line', 15, 0));
bw = imfill(bw, 'holes');
bw = bwareaopen(bw, 500);
[L,num] = bwlabel(bw);
vs = [];
for i = 1 : num
bwi = bw;
bwi(L~=i) = 0;
vi = mean(double(im2(logical(bwi))));
vs(i) = vi;
end
[~,ind] = max(vs);
bw(L~=ind) = 0;
[r,c] = find(logical(bw));
rect = [min(c) min(r) max(c)-min(c) max(r)-min(r)];
figure; imshow(im, []);
hold on; rectangle('Position', rect, 'EdgeColor', 'r', 'LineWidth', 2, 'LineStyle', '-');
end
  6 Comments
Zara Khan
Zara Khan on 21 Aug 2022
Edited: Zara Khan on 21 Aug 2022
@Image Analyst Thank you sir. But this method is not adaptive. Somehow working well for these attached images but when working 1320 images in batch the rectangle I am getting outside the image object means in background for some images. how to overcome this? Even I am not getting why these many filters are being used befire drawing the recctangles
[L,num] = bwlabel(bw);
vs = [];
for i = 1 : num
bwi = bw;
bwi(L~=i) = 0;
vi = mean(double(im2(logical(bwi))));
vs(i) = vi;
end
[~,ind] = max(vs);
bw(L~=ind) = 0;

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yanqi liu
yanqi liu on 27 Oct 2021
sir,use some basic method may be not the best choice,so may be consider some DeepLearning method,such as unet
clc; clear all; close all
urls={'https://ww2.mathworks.cn/matlabcentral/answers/uploaded_files/779463/img16.png',...
'https://ww2.mathworks.cn/matlabcentral/answers/uploaded_files/779458/img6.png',...
'https://ww2.mathworks.cn/matlabcentral/answers/uploaded_files/779453/img4.png',...
'https://ww2.mathworks.cn/matlabcentral/answers/uploaded_files/779448/img2.png',...
'https://ww2.mathworks.cn/matlabcentral/answers/uploaded_files/779443/img1.png',...
'https://ww2.mathworks.cn/matlabcentral/answers/uploaded_files/779438/img1%20(2).png'};
for k = 1 : length(urls)
im = imread(urls{k});
if ndims(im) == 3
im = rgb2gray(im);
end
im2 = imadjust(im,stretchlim(im),[]);
bw = imbinarize(im2,'adaptive','ForegroundPolarity','dark','Sensitivity',0.85);
bw = bwareaopen(bw, 100);
bw = imopen(bw, strel('line', 9, 90));
bw = imclose(bw, strel('line', 12, 0));
bw = imfill(bw, 'holes');
bw = bwareaopen(bw, 500);
[L,num] = bwlabel(bw);
vs = [];
for i = 1 : num
bwi = bw;
bwi(L~=i) = 0;
vi = mean(double(im2(logical(bwi))));
vs(i) = vi;
end
[~,ind] = max(vs);
bw(L~=ind) = 0;
bw = logical(bw);
bw = imfill(bw, 'holes');
bw = imclose(bw, strel('disk', 15));
[r,c] = find(logical(bw));
rect = [min(c) min(r) max(c)-min(c) max(r)-min(r)];
im2 = im;
im2(~bw) = 0;
figure; imshow(im2, []);
%hold on; rectangle('Position', rect, 'EdgeColor', 'r', 'LineWidth', 2, 'LineStyle', '-');
end
  16 Comments

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Zara Khan
Zara Khan on 27 Aug 2022
clc; clear all; close all
im=imread('https://in.mathworks.com/matlabcentral/answers/uploaded_files/1109360/img_4.png');
im2 = imadjust(im,stretchlim(im),[]);
bw = imbinarize(im2,'adaptive','ForegroundPolarity','dark','Sensitivity',0.85);
bw = bwareaopen(bw, 100);
bw = imopen(bw, strel('line', 9, 90));
bw = imclose(bw, strel('line', 15, 0));
bw = imfill(bw, 'holes');
bw = bwareaopen(bw, 500);
[L,num] = bwlabel(bw);
vs = [];
for i = 1 : num
bwi = bw;
bwi(L~=i) = 0;
vi = mean(double(im2(logical(bwi))));
vs(i) = vi;
end
[~,ind] = max(vs);
bw(L~=ind) = 0;
[r,c] = find(logical(bw));
rect = [min(c) min(r) max(c)-min(c) max(r)-min(r)];
figure; imshow(im, []);
hold on; rectangle('Position', rect, 'EdgeColor', 'r', 'LineWidth', 2, 'LineStyle', '-');
@Image Analyst @yanqi liu sir this algorithm not able to segement this gesture
  1 Comment
Image Analyst
Image Analyst on 27 Aug 2022
I am not a gesture recognition researcher. But I know that any successful algorithm will not just be one page of code. You need to use a robust algorithm already developed by specialists in the area who have published their algorithms. Go here to see a list of them:

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