Can any one correct this code to remove hair pixels??

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Pamela 2012-9-8

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评论： hamed abdulaziz 2013-9-29

Hi!! Can any on help to remove pixels hair from a dermoscopic image with DullRazor method. DullRazor performs the following steps: -It identifies the dark hair locations by a generalized grayscale morphological closing operation, -It verifies the shape of the hair pixels as thin and long structure, and replace the verified pixels by a bilinear interpolation, and -It smooths the replaced hair pixels with an adaptive median filter. I tried this but it's not correct:

image = im2double(imread('image1.bmp'));
figure, imshow(image);
grayscale = rgb2gray(image);
%get hairs using bottomhat filter
se = strel('disk',5);
hairs = imbothat(grayscale,se);
figure, imshow(hairs);

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回答（1 个）

Image Analyst 2012-9-8

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You need to find the hairs first. Binarize (threshold) and then use regionprops to identify long thin objects. Then use roifill() to replace those objects with the surrounding neighborhood background. I'm not sure what the median filter would gain you - I don't think it's necessary.

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Image Analyst 2012-9-8

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You can't, because you don't have separated hairs. They're all overlapping and crossing. You can try the code below. It's not perfect but ti gives you someplace to start.

% Demo to eliminate hairs.
% By ImageAnalyst
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.
fontSize = 14;
% Read in a standard MATLAB gray scale demo image.
folder = 'C:\Users\Mark\Documents\Temporary';
baseFileName = 'DullRazor.jpg';
% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);
if ~exist(fullFileName, 'file')
  % 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.', fullFileName);
    uiwait(warndlg(errorMessage));
    return;
  end
end
rgbImage = imread(fullFileName);
% Get the dimensions of the image.  numberOfColorBands should be = 3.
[rows columns numberOfColorBands] = size(rgbImage);
% Display the original color image.
subplot(2, 2, 1);
imshow(rgbImage, []);
% See if we can get rid of the hairs in the RGB image.
% rgbImage = imerode(rgbImage, true(5));
title('Original Color Image', 'FontSize', fontSize);
% Enlarge figure to full screen.
set(gcf, 'units','normalized','outerposition',[0 0 1 1]);
% Extract the individual red, green, and blue color channels.
redChannel = rgbImage(:, :, 1);
greenChannel = rgbImage(:, :, 2);
blueChannel = rgbImage(:, :, 3);
% Display the original color image.
subplot(2, 2, 2);
imshow(redChannel, []);
title('Red Channel', 'FontSize', fontSize);
subplot(2, 2, 3);
imshow(greenChannel, []);
title('Green Channel', 'FontSize', fontSize);
subplot(2, 2, 4);
imshow(blueChannel, []);
title('Blue Channel', 'FontSize', fontSize);
figure;
% Let's compute and display the histogram.
[pixelCount grayLevels] = imhist(redChannel);
subplot(2, 2, 1); 
bar(pixelCount);
grid on;
title('Histogram of red Channel', 'FontSize', fontSize);
xlim([0 grayLevels(end)]); % Scale x axis manually.
% Threshold the image
binaryImage = redChannel < 120;
binaryImage = imdilate(binaryImage, true(5));
% Display it.
subplot(2, 2, 2);
imshow(binaryImage, []);
title('Binary Image', 'FontSize', fontSize);
% Fill in the mask
redChannel = roifill(redChannel, binaryImage);
greenChannel = roifill(greenChannel, binaryImage);
blueChannel = roifill(blueChannel, binaryImage);
noHairImage = cat(3, redChannel, greenChannel, blueChannel);
% Display it.
subplot(2, 2, 3);
imshow(noHairImage, []);
title('No Hair Image', 'FontSize', fontSize);