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从信号图像(RGB)中去除背景噪声

cv2 rgb image-processing python

bit_scientist · 技术社区 · 5 年前

我有一些信号图像:

如您所知,其中一些包含彩色信号,而另一些只是灰色/黑色信号。只是。这意味着我需要删除图像中除信号以外的所有内容。

我检查了虚线、虚线、实线(顶部和底部)是否具有接近0的相同RGB值;0;0(例如:0;0;0, 2;2;2; 或8;8;8) 在RGB方面。

但是,该过程将删除信号像素值相同的信号。这种情况主要发生在黑色信号上(例如前两个样本)。

我没有要求任何代码解决这个问题。我想对如何成功提取原始信号有不同的看法。

我期待着你的想法,见解和来源。谢谢

注意:我所有的图片(大约3k)都在一个文件夹中,我将应用一个通用算法来完成这项任务。

0 回复 | 直到 5 年前

Rotem 5 年前

您可以使用 Hough transform .
找到这些线后,就可以简单地将它们删除。

删除线只是第一阶段,但它看起来像一个很好的起点。。。
保持彩色像素(如您所建议的)也是一项简单的任务。

close all
clear

origI = imread('I.png'); %Read image
I = imbinarize(rgb2gray(origI)); %Convert to binary
I = ~I; %Invert - the line color should be white.

%Apply hough transform: Find lines with angles very close to 0 degrees and with angles close to 90 degrees.
[H,theta,rho] = hough(I, 'RhoResolution', 1, 'Theta', [-0.3:0.02:0.3, -90:0.02:-89.7, 89.7:0.02:89.98]);
P = houghpeaks(H, numel(H), 'Threshold', 0.1, 'NHoodSize', [11, 1]); %Use low thresholds
lines = houghlines(I,theta,rho,P,'FillGap',25,'MinLength',200); %Fill large gaps and keep only the long lines.

%Plot the lines for debugging, and erase them by drawing black lines over them
J = im2uint8(I);
figure, imshow(I), hold on
for k = 1:length(lines)
   xy = [lines(k).point1; lines(k).point2];
   plot(xy(:,1),xy(:,2),'LineWidth',2,'Color','green');

   % Plot beginnings and ends of lines
   plot(xy(1,1),xy(1,2),'x','LineWidth',2,'Color','yellow');
   plot(xy(2,1),xy(2,2),'x','LineWidth',2,'Color','red');

   % Draw black line over each line.
   J = insertShape(J, 'Line', [xy(1,1), xy(1,2), xy(2,1), xy(2,2)], 'Color', 'Black');
end

%Covert J image to binary (because MATLAB function insertShape returns RGB output).
J = imbinarize(rgb2gray(J));
figure, imshow(J)

%Color mask: 1 where color is not black or white.
I = double(origI);
C = (abs(I(:,:,1) - I(:,:,2)) > 20) | (abs(I(:,:,1) - I(:,:,3)) > 20) | (abs(I(:,:,2) - I(:,:,3)) > 20);

figure, imshow(C)

%Build a mask that combines "lines" mask and "color" mask.
Mask = J | C;
Mask = cat(3, Mask, Mask, Mask);

%Put white color where mask value is 0.
K = origI;
K(~Mask) = 255;

figure, imshow(K)

检测到的行:

删除行后的结果:

如你所见,还有剩菜。
我对上述结果应用了第二次迭代(相同的代码)。

你可以试着用形态学的方法去除残羹剩饭。

迭代所有PNG图像文件:

将代码放入 m 文件(MATLAB脚本文件)。
放置 米 文件位于PNG图像文件的同一文件夹中。

代码如下:

%ExtractSignals.m

close all
clear

%List all PNG files in the working directory (where ExtractSignals.m is placed).
imagefiles = dir('*.png');
nfiles = length(imagefiles);

result_images = cell(1, nfiles); %Allocate cell array for storing output images

for ii = 1:nfiles
    currentfilename = imagefiles(ii).name; %PNG file name

    origI = imread(currentfilename); %Read image

    %Verify origI is in RGB format (just in case...)
    if (size(origI, 3) ~= 3)
        error([currentfilename, ' is not RGB image format!']);
    end

    I = imbinarize(rgb2gray(origI)); %Convert to binary
    I = ~I; %Invert - the line color should be white.

    %Apply hough transform: Find lines with angles very close to 0 degrees and with angles close to 90 degrees.
    [H,theta,rho] = hough(I, 'RhoResolution', 1, 'Theta', [-0.3:0.02:0.3, -90:0.02:-89.7, 89.7:0.02:89.98]);
    P = houghpeaks(H, numel(H), 'Threshold', 0.1, 'NHoodSize', [11, 1]); %Use low thresholds
    lines = houghlines(I,theta,rho,P,'FillGap',25,'MinLength',200); %Fill large gaps and keep only the long lines.

    %Plot the lines for debugging, and erase them by drawing black lines over them
    J = im2uint8(I);
    %figure, imshow(I), hold on
    for k = 1:length(lines)
        xy = [lines(k).point1; lines(k).point2];
        %plot(xy(:,1),xy(:,2),'LineWidth',2,'Color','green');

        % Plot beginnings and ends of lines
        %plot(xy(1,1),xy(1,2),'x','LineWidth',2,'Color','yellow');
        %plot(xy(2,1),xy(2,2),'x','LineWidth',2,'Color','red');

        % Draw black line over each line.
        J = insertShape(J, 'Line', [xy(1,1), xy(1,2), xy(2,1), xy(2,2)], 'Color', 'Black');
    end

    %Covert J image to binary (because MATLAB function insertShape returns RGB output).
    J = imbinarize(rgb2gray(J));
    %figure, imshow(J)

    %Color mask: 1 where color is not black or white.
    I = double(origI);
    C = (abs(I(:,:,1) - I(:,:,2)) > 20) | (abs(I(:,:,1) - I(:,:,3)) > 20) | (abs(I(:,:,2) - I(:,:,3)) > 20);

    %figure, imshow(C)

    %Build a mask that combines "lines" mask and "color" mask.
    Mask = J | C;
    Mask = cat(3, Mask, Mask, Mask);

    %Put white color where mask value is 0.
    K = origI;
    K(~Mask) = 255;

    %figure, imshow(K)

    %Second iteration - applied by "copy and paste" of the above code (it is recommended to use a function instead).
    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
    origI = K; %Set origI to the result of the first iteration

    I = imbinarize(rgb2gray(origI)); %Convert to binary
    I = ~I; %Invert - the line color should be white.

    %Apply hough transform: Find lines with angles very close to 0 degrees and with angles close to 90 degrees.
    [H,theta,rho] = hough(I, 'RhoResolution', 1, 'Theta', [-0.3:0.02:0.3, -90:0.02:-89.7, 89.7:0.02:89.98]);
    P = houghpeaks(H, numel(H), 'Threshold', 0.1, 'NHoodSize', [11, 1]); %Use low thresholds
    lines = houghlines(I,theta,rho,P,'FillGap',25,'MinLength',200); %Fill large gaps and keep only the long lines.

    %Plot the lines for debugging, and erase them by drawing black lines over them
    J = im2uint8(I);
    %figure, imshow(I), hold on
    for k = 1:length(lines)
        xy = [lines(k).point1; lines(k).point2];
        % Draw black line over each line.
        J = insertShape(J, 'Line', [xy(1,1), xy(1,2), xy(2,1), xy(2,2)], 'Color', 'Black');
    end

    %Covert J image to binary (because MATLAB function insertShape returns RGB output).
    J = imbinarize(rgb2gray(J));
    %figure, imshow(J)

    %Color mask: 1 where color is not black or white.
    I = double(origI);
    C = (abs(I(:,:,1) - I(:,:,2)) > 20) | (abs(I(:,:,1) - I(:,:,3)) > 20) | (abs(I(:,:,2) - I(:,:,3)) > 20);

    %figure, imshow(C)

    %Build a mask that combines "lines" mask and "color" mask.
    Mask = J | C;
    Mask = cat(3, Mask, Mask, Mask);

    %Put white color where mask value is 0.
    K = origI;
    K(~Mask) = 255;
    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

    %Store result image in a cell array
    result_images{ii} = K;
end

%Display all result images
for ii = 1:nfiles
    figure;
    imshow(result_images{ii});
    title(['Processed ', imagefiles(ii).name]);
end