i am able to overlap the binary image with the original RGB image. Through the following code.
inImage = imresize(imread('1.jpg'),0.25);
%imwrite(inImage,'original.jpg');
inImage = skyremoval(inImage);
greyImage = rgb2gray(inImage);
thresh1 = 200;
whiteLayer = greyImage > thresh1;
thresh2 = 125;
lightgreyLayer = greyImage > thresh2 & greyImage <= thresh1;
layer1 = whiteLayer*200;
layer2 = lightgreyLayer*125;
G = layer1 + layer2;
% figure,imshow(G);
se = strel('disk', 15);
Io = imopen(G, se);
figure,imshow(Io);
f = find(Io==0);
mask(:,:,1) = f; % For the red plane
% mask(:,:,2) = f; % For the green plane
% mask(:,:,3) = f; % For the blue plane
inImage(mask)=0;
I = inImage;
figure,imshow(I);
The following are the images.
Here.The first is the binary image derived from the original, second is the original and the third is the result after overlaping both binary and rgb images, by the code given above. As you can see the problem i am facing is that the part except road is cyan all i want is the part which is not road to be black. How can i do that?
Please alter my code if you can help. Thank you.
You don't need the find command, since you can index with a binary image.
Instead of
f = find(Io==0);
mask(:,:,1) = f; % For the red plane
% mask(:,:,2) = f; % For the green plane
% mask(:,:,3) = f; % For the blue plane
inImage(mask)=0;
I = inImage;
figure,imshow(I);
you can write
mask = repmat(Io==0,1,1,3); %# 1 wherever mask is false
I = inImage;
I(mask) = 0;
figure,imshow(I);
Related
i want to make a second axis for the same colorbar of an false color image. the second scale should follow this convention : [new values] = Log10([old values]/108000)/-0.4 . i have this code for the first axis:
C = 10
hFig = figure('Name','False Color Luminance Map', 'ToolBar','none','MenuBar','none');
% Create/initialize default colormap of jet.
cmap = parula(16); % or 256, 64, 32 or whatever.
% Now make lowest values show up as black.
cmap(1,:) = 0;
% Now make highest values show up as white.
cmap(end,:) = 1;
imshow(J,'Colormap',cmap) % show Image in false color
colorbar % add colorbar
h = colorbar; % define colorbar as variable
caxis auto
y_Scl = (1/C);
yticks = get(h,'YTick');
set(h,'YTickLabel',sprintfc('%g', [yticks.*y_Scl]))
in a previous post here i got this lines for an second axis:
BarPos = get(hBar1,'position');
ylabel(hBar1,'label','FontSize',12);
haxes = axes('position',BarPos,'color','none','ytick',0:5:15,'ylim',[0 15],'xtick',[]);
how can i make the second axis use the the yticks of the first axis as an input for the convention?
EDIT: here is what i came up with. the thing is the values are wrong :/
fname='IMG_0041'; % select target image
C = 1000; % Constant to adjust image
K = 480; % Cameraconstant
RGB = imread([fname, '.tif']);% Read Image as tif
info = imfinfo([fname,'.CR2']); % get Metadata from CR2
x = info.DigitalCamera; % get EXIF
t = getfield(x, 'ExposureTime');% save ExposureTime
f = getfield(x, 'FNumber'); % save FNumber
S = getfield(x, 'ISOSpeedRatings');% save ISOSpeedRatings
date = getfield(x,'DateTimeOriginal'); % save DateTimeOriginal
I = rgb2gray(RGB); % convert Image to greyscale
% N_s = K*(t*S)/power(f,2))*L
L = power(f,2)/(K*t*S)*C; % calculate L/N_s
J = immultiply(I,L);
hFig = figure('Name','False Color Luminance Map', 'ToolBar','none', 'MenuBar','none');
% Create/initialize default colormap of jet.
cmap = parula(16); % or 256, 64, 32 or whatever.
% Now make lowest values show up as black.
cmap(1,:) = 0;
% Now make highest values show up as white.
cmap(end,:) = 1;
imshow(J,'Colormap',cmap) % show Image in false color
colorbar % add colorbar
h = colorbar; % define colorbar as variable
caxis auto
y_Scl = (1/C);
yticks = get(h,'YTick');
set(h,'YTickLabel',sprintfc('%g', [yticks.*y_Scl]))
BarPos = get(h,'position');
haxes = axes('position',BarPos,'color','none','ylim',[0 150]);
set(haxes,'YTickLabel', sprintfc('%g', log10(yticks.*y_Scl/108000)/-0.4));
https://www.sendspace.com/file/39wwm9 -> files for testing the code
I have two polygon images defined by 25 control points. I want to replace one polygon by another one in matlab. Below is an example of TC and BP.
I have added the code. I am not happy with the output texture in the replaced area. Also, I found the that if the polygon shape of the second image is smaller than the first image polygon shape then the output looks very bad.
clc;clear all;close all
im_original = imread('tc.jpg');
im_original=im2double(im_original);
%% ROI (X,Y) coordinates, variable name (pt_original)
load('tc.mat');
im_morphed = imread('bp.jpg');
img_morphed=im2double(im_morphed);
%% ROI (X,Y) coordinates, variable name (pt_morphed)
load('bp.mat');
%% Replace Face
[img_proc,mask] = defineRegion(im_original,pt_original);
img_morphed_proc = histeq_rgb(img_morphed, im_original, mask, mask);
sigma = 5;
se = strel('square',sigma);
mask = imerode(mask,se);
w = fspecial('gaussian',[50 50],sigma);
mask = imfilter(double(mask),w);
img_result = bsxfun(#times,double(img_morphed_proc),double(mask)) + bsxfun(#times,double(im_original),double(1-mask));
imshow(img_result)
function [img_proc,mask] = defineRegion(img, landmark)
sz = size(img);
k =convhull(landmark(:,2),landmark(:,1));
[YY,XX] = meshgrid(1:sz(1),1:sz(2));
in = inpolygon(XX(:),YY(:),landmark(k,1),landmark(k,2));
mask = reshape(in,[sz(2),sz(1)])';
img_proc = bsxfun(#times,im2double(img),double(mask));
end
function img_proc = histeq_rgb(img_src, img_dest, mask_src, mask_dest)
img_proc = img_src;
for i = 1 : 3
tmp_src = img_src(:,:,i);
tmp_src = tmp_src(mask_src);
tmp_dest = img_dest(:,:,i);
tmp_dest = tmp_dest(mask_dest);
t = histeq(tmp_src,imhist(tmp_dest));
tmp_proc = img_proc(:,:,i);
tmp_proc(mask_src) = t;
img_proc(:,:,i) = tmp_proc;
end
end
Output Image
I have the following function that is successful in creating a grey circular mask over the image input, such that the new image is a grey border around a circular image. Example: Grey circular mask.
All I want to do is make the mask a very specific green, but I haven't been successful.
Here is the code:
function [newIm] = myCircularMask(im)
%Setting variables
rad = size(im,1)/2.1; %Radius of the circle window
im = double(im);
[rows, cols, planes]= size(im);
newIm = zeros(rows, cols, planes);
%Generating hard-edged circular mask with 1 inside and 0 outside
M = rows;
[X,Y] = meshgrid(-M/2:1:(M-1)/2, -M/2:1:(M-1)/2);
mask = double(zeros(M,M));
mask(X.^2 + Y.^2 < rad^2) = 1;
% Soften edge of mask
gauss = fspecial('gaussian',[12 12],0.1);
mask = conv2(mask,gauss,'same');
% Multiply image by mask, i.e. x1 inside x0 outside
for k=1:planes
newIm(:,:,k) = im(:,:,k).*mask;
end
% Make mask either 0 inside or -127 outside
mask = (abs(mask-1)*127);
% now add mask to image
for k=1:planes
newIm(:,:,k) = newIm(:,:,k)+mask;
end
newIm = floor(newIm)/255;
The type of green I would like to use is of RGB values [59 178 74].
I'm a beginner with MATLAB, so any help would be greatly appreciated.
Cheers!
Steve
After masking your image, create a color version of your mask:
% test with simple mask
mask = ones(10,10);
mask(5:7,5:7)=0;
% invert mask, multiply with rgb-values, make rgb-matrix:
r_green=59/255; g_green=178/255; b_green=74/255;
invmask=(1-mask); % use mask with ones/zeroes
rgbmask=cat(3,invmask*r_green,invmask*g_green,invmask*b_green);
Add this to your masked image.
Edit:
function [newIm] = myCircularMask(im)
%Setting variables
rad = size(im,1)/2.1; %Radius of the circle window
im = double(im);
[rows, cols, planes]= size(im);
newIm = zeros(rows, cols, planes);
%Generating hard-edged circular mask with 1 inside and 0 outside
M = rows;
[X,Y] = meshgrid(-M/2:1:(M-1)/2, -M/2:1:(M-1)/2);
mask = double(zeros(M,M));
mask(X.^2 + Y.^2 < rad^2) = 1;
% Soften edge of mask
gauss = fspecial('gaussian',[12 12],0.1);
mask = conv2(mask,gauss,'same');
% Multiply image by mask, i.e. x1 inside x0 outside
for k=1:planes
newIm(:,:,k) = im(:,:,k).*mask;
end
% Here follows the new code:
% invert mask, multiply with rgb-values, make rgb-matrix:
r_green=59/255; g_green=178/255; b_green=74/255;
invmask=(1-mask); % use mask with ones/zeroes
rgbmask=cat(3,invmask*r_green,invmask*g_green,invmask*b_green);
newIm=newIm+rgbmask;
Note that I haven't been able to test my suggestion, so there might be errors.
I am using the following code in MATLAB to find the rectangle containing a car's license plate:
clc
clear
close all
%Open Image
I = imread('plate_1.jpg');
figure, imshow(I);
%Gray Image
Ib = rgb2gray(I);
figure,
subplot(1,2,1), imshow(Ib);
%Enhancement
Ih = histeq(Ib);
subplot(1,2,2), imshow(Ih);
figure,
subplot(1,2,1), imhist(Ib);
subplot(1,2,2), imhist(Ih);
%Edge Detection
Ie = edge(Ih, 'sobel');
figure,
subplot(1,2,1), imshow(Ie);
%Dilation
Id = imdilate(Ie, strel('diamond', 1));
subplot(1,2,2), imshow(Id);
%Fill
If = imfill(Id, 'holes');
figure, imshow(If);
%Find Plate
[lab, n] = bwlabel(If);
regions = regionprops(lab, 'All');
regionsCount = size(regions, 1) ;
for i = 1:regionsCount
region = regions(i);
RectangleOfChoice = region.BoundingBox;
PlateExtent = region.Extent;
PlateStartX = fix(RectangleOfChoice(1));
PlateStartY = fix(RectangleOfChoice(2));
PlateWidth = fix(RectangleOfChoice(3));
PlateHeight = fix(RectangleOfChoice(4));
if PlateWidth >= PlateHeight*3 && PlateExtent >= 0.7
im2 = imcrop(I, RectangleOfChoice);
figure, imshow(im2);
end
end
Plates all have white backgrounds. Currently,I use the rectangles' ratio of width to height to select candidate regions for output. This gives the plate rectangle in addition to several other irrelevant ones in the case of a white car. What method can I use to get only one output: the license plate?
Also, I don't find a plate at all when I run the code on a black car. Maybe that's because the car's color is the same as the plate edge.
Are there any alternatives to edge detection to avoid this problem?
Try this !!!
I = imread('http://8pic.ir/images/88146564605446812704.jpg');
im=rgb2gray(I);
sigma=1;
f=zeros(128,128);
f(32:96,32:96)=255;
[g3, t3]=edge(im, 'canny', [0.04 0.10], sigma);
se=strel('rectangle', [1 1]);
BWimage=imerode(g3,se);
gg = imclearborder(BWimage,8);
bw = bwareaopen(gg,200);
gg1 = imclearborder(bw,26);
imshow(gg1);
%Dilation
Id = imdilate(gg1, strel('diamond', 1));
imshow(Id);
%Fill
If = imfill(Id, 'holes');
imshow(If);
%Find Plate
[lab, n] = bwlabel(If);
regions = regionprops(lab, 'All');
regionsCount = size(regions, 1) ;
for i = 1:regionsCount
region = regions(i);
RectangleOfChoice = region.BoundingBox;
PlateExtent = region.Extent;
PlateStartX = fix(RectangleOfChoice(1));
PlateStartY = fix(RectangleOfChoice(2));
PlateWidth = fix(RectangleOfChoice(3));
PlateHeight = fix(RectangleOfChoice(4));
if PlateWidth >= PlateHeight*1 && PlateExtent >= 0.7
im2 = imcrop(I, RectangleOfChoice);
%figure, imshow(I);
figure, imshow(im2);
end
end
I'm using normxcorr2 to find the area that exactly match with my pattern and i also want to find the other area(in the red rectangle) that is look like the pattern. I think it will be works if i can find the next maximum and so on and that value must not in the first maximum area or the first one that it has been detected but i can't do it. Or if you have any idea that using normxcorr2 to find the others area please advise me, I don't have any idea at all.
Here's my code. I modified from this one http://www.mathworks.com/products/demos/image/cross_correlation/imreg.html
onion = imread('pattern103.jpg'); %pattern image
peppers = imread('rsz_1jib-159.jpg'); %Original image
onion = rgb2gray(onion);
peppers = rgb2gray(peppers);
%imshow(onion)
%figure, imshow(peppers)
c = normxcorr2(onion,peppers);
figure, surf(c), shading flat
% offset found by correlation
[max_c, imax] = max(abs(c(:)));
[ypeak, xpeak] = ind2sub(size(c),imax(1));
corr_offset = [(xpeak-size(onion,2))
(size(onion,1)-ypeak)]; %size of window show of max value
offset = corr_offset;
xoffset = offset(1);
yoffset = offset(2);
xbegin = round(xoffset+1); fprintf(['xbegin = ',num2str(xbegin)]);fprintf('\n');
xend = round(xoffset+ size(onion,2));fprintf(['xend = ',num2str(xbegin)]);fprintf('\n');
ybegin = round(yoffset+1);fprintf(['ybegin = ',num2str(ybegin)]);fprintf('\n');
yend = round(yoffset+size(onion,1));fprintf(['yend = ',num2str(yend)]);fprintf('\n');
% extract region from peppers and compare to onion
extracted_onion = peppers(ybegin:yend,xbegin:xend,:);
if isequal(onion,extracted_onion)
disp('pattern103.jpg was extracted from rsz_org103.jpg')
end
recovered_onion = uint8(zeros(size(peppers)));
recovered_onion(ybegin:yend,xbegin:xend,:) = onion;
figure, imshow(recovered_onion)
[m,n,p] = size(peppers);
mask = ones(m,n);
i = find(recovered_onion(:,:,1)==0);
mask(i) = .2; % try experimenting with different levels of
% transparency
% overlay images with transparency
figure, imshow(peppers(:,:,1)) % show only red plane of peppers
hold on
h = imshow(recovered_onion); % overlay recovered_onion
set(h,'AlphaData',mask)