I need to extract the road sign from an image. Can someone help me with this as I am new to matlab.
MATLAB: Convert red portion to white and the background to black . Second part is to detect road sign and put bounding box on it.
classificationComputer Vision Toolboxdigital image processingimage acquisitionimage analysisimage segmentationMATLABroad signs
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Can't you just erase above and below those lines?
rgbImage(1 : 500, :, :) = 0;rgbImage(3500 : end, :, :) = 0;The code below works for this image. Of course it may not work if you change the lighting, exposure, camera angle, F-stop, or clutter (other stuff) in the image, and would need adaptation for those cases.
% Code to analyze grinding wheel
clc; % Clear the command window.
close all; % Close all figures (except those of imtool.)
clearvars;workspace; % Make sure the workspace panel is showing.
format long g;format compact;fontSize = 16;%=======================================================================================
% Read in image.
fullFileName = fullfile(pwd, 'annular_orig.jpg');[folder, baseFileName, ext] = fileparts(fullFileName);rgbImage = imread(fullFileName);% Shrink it to speed it up
% rgbImage = imresize(rgbImage, 0.75);
% Get the dimensions of the image.
[rows, columns, numberOfColorChannels] = size(rgbImage);% Display the original image.
subplot(2, 2, 1);imshow(rgbImage, []);axis on;caption = sprintf('Original Color Image "%s"', baseFileName);title(caption, 'FontSize', fontSize, 'Interpreter', 'None');drawnow;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')% Get mask for outer gray, and inner blue parts of the wheel by doing color segmentations.
[wheelMask,maskedRGBImage] = createMaskForWholeWheel(rgbImage);[blueMask,maskedRGBImage] = createMaskForBlueCenter(rgbImage);% Clean up noise by filling holes and taking largest blob only.
wheelMask = imfill(wheelMask, 'holes');wheelMask = bwareafilt(wheelMask, 1);blueMask = imfill(blueMask, 'holes');blueMask = bwareafilt(blueMask, 1);% Display the images.
subplot(2, 2, 2);imshow(wheelMask);axis on;title('Total Wheel Mask', 'FontSize', fontSize, 'Interpreter', 'None');subplot(2, 2, 3);imshow(blueMask);axis on;title('Blue Center Mask', 'FontSize', fontSize, 'Interpreter', 'None');drawnow;% Get the ring mask
ringMask = wheelMask & ~blueMask;% Display the image.
subplot(2, 2, 4);imshow(ringMask);axis on;title('Ring Mask', 'FontSize', fontSize, 'Interpreter', 'None');drawnow;% Find boundaries
boundaries = bwboundaries(ringMask);% Display the original image with mask boundary over it.
figure;imshow(rgbImage, []);axis on;caption = sprintf('Color Image with Boundary');title(caption, 'FontSize', fontSize, 'Interpreter', 'None');drawnow;hp = impixelinfo(); % Set up status line to see values when you mouse over the image.% Plot boundaries
hold on;numberOfBoundaries = size(boundaries, 1);for k = 1 : numberOfBoundaries thisBoundary = boundaries{k}; plot(thisBoundary(:,2), thisBoundary(:,1), 'r', 'LineWidth', 3);endhold off;% Get the equivalent circular diameters.
propsWheel = regionprops(wheelMask, 'EquivDiameter');wheelDiameter = propsWheel.EquivDiameterpropsBlue = regionprops(blueMask, 'EquivDiameter');blueDiameter = propsBlue.EquivDiameter% Get the area of the ring and put it up on the image.
ringArea = sum(ringMask(:));message = sprintf('Area of ring = %d pixels.\nAverage Diameter of Entire Wheel = %.1f pixels.\nAverage Diameter of Blue Part = %.1f pixels.\nAverage Thickness of Edge = %.1f pixels.', ... ringArea, wheelDiameter, blueDiameter, wheelDiameter-blueDiameter);text(20, 150, message, 'FontSize', fontSize, 'Color', 'y', 'FontWeight', 'bold', 'VerticalAlignment', 'top');function [BW,maskedRGBImage] = createMaskForWholeWheel(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 15-Aug-2018
%------------------------------------------------------
% Convert RGB image to chosen color space
I = rgb2hsv(RGB);% Define thresholds for channel 1 based on histogram settings
channel1Min = 0.363;channel1Max = 0.855;% Define thresholds for channel 2 based on histogram settings
channel2Min = 0.000;channel2Max = 1.000;% Define thresholds for channel 3 based on histogram settings
channel3Min = 0.000;channel3Max = 1.000;% 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;endfunction [BW,maskedRGBImage] = createMaskForBlueCenter(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 15-Aug-2018%------------------------------------------------------% Convert RGB image to chosen color spaceI = rgb2hsv(RGB);% Define thresholds for channel 1 based on histogram settingschannel1Min = 0.569;channel1Max = 0.671;% Define thresholds for channel 2 based on histogram settingschannel2Min = 0.229;channel2Max = 1.000;% Define thresholds for channel 3 based on histogram settingschannel3Min = 0.251;channel3Max = 1.000;% Create mask based on chosen histogram thresholdssliderBW = (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
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