MATLAB: Remove noise from screw image

image processingImage Processing Toolboxmachine visionnoise removal

The screw image shown below has some dust/fur on the screw thread. What are the ways to remove those noise and produce a new image with clear outline of the screw?

I tried it myself and came out result as shown below.

Some of the noises are still not removed. I have also attached my codes as shown below.

clc
clear
close all
%% Read
A = imread('20.bmp');
%% Turn into grayscale
I0 = rgb2gray(A);
%% Crop
I1 = imcrop(I0,[1,78,710-1,410-78]);
%% Histogram
[pixelCount, grayLevels] = imhist(I0);
%% Adjustment
I2 = imadjust(I1);
I3 = medfilt2(I2);
ThresholdValue = graythresh(I3);
I4 = imbinarize(I3, ThresholdValue);
I5 = edge(I4,'Sobel');

Best Answer

The screw and the threads are the black thing and the dust is the lighter things on it. I think you are just using the wrong threshold. You can adjust it in imbinarize(), or you can do it interactively with my interactive thresholding app in my File Exchange.

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MATLAB: Straightening Image from RF data

Do you have a calibration from RF signal to kilograms, and from pixels to µm? And are you sure you really need to straighten the thing? Why isn't just going column by column enough? If you did, I'd probably start by thresholding and then going column by column to get the midpoint, like this code:

clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
imtool close all;  % Close all imtool figures.
clear;  % Erase all existing variables.
workspace;  % Make sure the workspace panel is showing.
format longg;
format compact;
fontSize = 20;
% Read in a gray scale demo image.
folder = 'C:\Users\Srikanta\Documents';
baseFileName = 'tissue.png';
% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);
% Check if file exists.
if ~exist(fullFileName, 'file')
  % File doesn't exist -- didn't find it there.  Check the search path for it.
  fullFileName = baseFileName; % No path this time.
  if ~exist(fullFileName, '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);
% Crop it.
grayImage = rgb2gray(imcrop(grayImage, [90 140 400 110]));
% Get the dimensions of the image.  
% numberOfColorBands should be = 1.
[rows columns numberOfColorBands] = size(grayImage);
% Display the original gray scale image.

subplot(2, 2, 1);
imshow(grayImage, []);
title('Original Grayscale Image', 'FontSize', fontSize);
% Enlarge figure to full screen.
set(gcf, 'units','normalized','outerposition',[0 0 1 1]);
% Give a name to the title bar.
set(gcf,'name','Demo by ImageAnalyst','numbertitle','off') 
% Let's compute and display the histogram.
[pixelCount grayLevels] = imhist(grayImage);
% Suppress the 0 bin:
pixelCount(1) = 0;
subplot(2, 2, 2); 
bar(pixelCount);
grid on;
title('Histogram of original image', 'FontSize', fontSize);
xlim([0 grayLevels(end)]); % Scale x axis manually.
% Get the binary image
binaryImage = grayImage > 10;
% Display the original gray scale image.
subplot(2, 2, 3);
imshow(binaryImage, []);
title('Binary Image', 'FontSize', fontSize);
% Smooth it out some and clean it up.
binaryImage = imclose(binaryImage, true(5));
binaryImage = imfill(binaryImage, 'holes')
subplot(2, 2, 4);
imshow(binaryImage, []);
title('Cleaned Binary Image', 'FontSize', fontSize);
% Get the midpoints
topRow = zeros(columns, 1);
bottomRow = zeros(columns, 1);
midpoints = zeros(columns, 1);
for column = 1 : columns
  oneColumn = binaryImage(:, column);
  if sum(oneColumn) > 0
    topRow(column) = find(binaryImage(:, column), 1, 'first');
    bottomRow(column) = find(binaryImage(:, column), 1, 'last');
    midpoints(column) = (topRow(column) + bottomRow(column)) / 2;
  end
end
hold on;
plot(1:columns, midpoints, 'r-', 'LineWidth', 2);

After that it gets tricky, though I've done it. You can go along the midpoint curve fitting a short stretch of it to a slowly varying curve and take perpendicular lines to get the profile. I posted code for that here just within the last two months or so.

MATLAB: Remove parts from Image and Fill Parts

Pretty easy. Threshold, fill holes, take the 3 largest.

Solution below. Adapt as needed.

% Initialization steps.
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 = 14;
filename = fullfile(pwd, 'image_1.jpg');
grayImage = imread(filename);
if ndims(grayImage) == 3
	% It's really an RGB image, not a gray scale image.  
	% Convert to gray scale
	grayImage = rgb2gray(grayImage);
end
subplot(2, 3, 1);
imshow(grayImage, []);
title('Original Image', 'FontSize', fontSize);
% Threshold
subplot(2, 3, 2);
imhist(grayImage);
grid on;
title('Histogram', 'FontSize', fontSize);
mask = grayImage < 128; % or whatever value works
subplot(2, 3, 3);
imshow(mask, []);
title('Initial Binary Image', 'FontSize', fontSize);
% Fill Holes
mask = imfill(mask, 'holes');
subplot(2, 3, 4);
imshow(mask, []);
title('After holes filled', 'FontSize', fontSize);
% Take 3 largest blobs then invert intensity.
mask = ~bwareafilt(mask, 3);
subplot(2, 3, 5);
imshow(mask, []);
title('Final Image Showing 3 Largest', 'FontSize', fontSize);

Best Answer

Related Solutions

MATLAB: Straightening Image from RF data

MATLAB: Remove parts from Image and Fill Parts

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