Currently, I try to draw a rectangular box around a white object with a label indicating its size.
I want create 4 categories of sizes:
Don't have
Small
Medium
Big
I don't have clue how to create this.
use insertObjectAnnotation:
% generate image
bw = zeros(1000);
[xg,yg] = meshgrid(1:1000);
rads = 10:20:100;
for ii = 1:length(rads)
r = rads(ii);
c = randi([1+r,1000-r],[1,2]);
bw = bw | ( ((xg - c(1)).^2 + (yg - c(2)).^2) < r^2);
end
% extract region properties
props = regionprops(bw,'Area','BoundingBox');
% add labels
sizes = [0,2000,6000,10000];
labels = {'tiny','small','medium','large'};
colors = autumn(numel(labels));
bw = double(bw);
for ii = 1:numel(props)
labelidx = find(props(ii).Area > sizes,1,'last');
bw = insertObjectAnnotation(bw,'rectangle',...
props(ii).BoundingBox,labels{labelidx},...
'Color',colors(labelidx,:),'FontSize',32);
end
imshow(bw);
EDIT: applying this to the OP's image:
Related
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
suppose that I have the following code:
clc
clear
band1 = imread('C:\Users\sepideh\Desktop\DrAkhundzadeh\Bands\band1.tif');
band2 = imread('C:\Users\sepideh\Desktop\DrAkhundzadeh\Bands\band2.tif');
band3 = imread('C:\Users\sepideh\Desktop\DrAkhundzadeh\Bands\band3.tif');
band4 = imread('C:\Users\sepideh\Desktop\DrAkhundzadeh\Bands\band4.tif');
band5 = imread('C:\Users\sepideh\Desktop\DrAkhundzadeh\Bands\band5.tif');
band7 = imread('C:\Users\sepideh\Desktop\DrAkhundzadeh\Bands\band7.tif');
Vegetation = band4-band3;
Oxide = band3-band1;
Hydroxyl = band5-band7;
%Normalize
NormalizedVegetation = ( Vegetation - min(min(Vegetation)))*255/(max(max(Vegetation)) - min(min(Vegetation)));
NormalizedOxide = ( Oxide - min(min(Oxide)))*255/(max(max(Oxide)) - min(min(Oxide)));
NormalizedHydroxyl = ( Hydroxyl - min(min(Hydroxyl)))*255/(max(max(Hydroxyl)) - min(min(Hydroxyl)));
FalseColor(:,:,1) = NormalizedVegetation;
FalseColor(:,:,2) = NormalizedOxide;
FalseColor(:,:,3) = NormalizedHydroxyl;
RGBIMAG = uint8(FalseColor);
imshow(RGBIMAG);
my problem is with the line:
RGBIMAG = uint8(FalseColor);
which causes all the image to get darked. How can I tell matlab that each level of the 3 dimensional matrix are different band of an RGB image without changing its elements.
For converting to uint8, you must use:
RGBIMAG = im2uint8(FalseColor);
That function receives ur double array( values btw 0-1 ) and converts them to RGB values in the range (0, 255).
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)
How can i separate the image as a three region(dark, mid, bright)?any matlab commands are available for that?
The image processing toolbox has some options for segmenting images based on color. More information here. If you only need to select pixels based on intensity you can use Boolean operators. Here's an example of that approach:
% create an example image with three regions of intensity
im = ones(100,100);
im(1:25, 1:30) = 256;
im(75:end, 7:end) = 128;
% add some random noise
im = im + 10*rand(size(im));
% display image
figure
subplot(2,2,1)
image(im)
colormap gray
% segment image based on intensity
bottomThird = 256/3;
topThird = 2*256/3;
index1 = find(im < bottomThird);
index2 = find(and((im > bottomThird),(im <topThird)));
index3 = find(im > topThird);
%create images for each segmented region
im1 = ones(size(im));
im2 = ones(size(im));
im3 = ones(size(im));
im1(index1) = 0;
im2(index2) = 0;
im3(index3) = 0;
%display sub-regions
subplot(2,2,2)
imagesc(im1)
subplot(2,2,3)
imagesc(im2)
subplot(2,2,4)
imagesc(im3)
I need some help with RGB capture in a image.
I am using impixel to manualy get RGB from a picture, but i would like to create a grid of let's say 20x20 px boxes where it will automatically tell me for each box a RGB value. So in a picture lets say i have 20 boxes it will tell me 20 RGB values. Yeah an if there is 20% or more of white space that it ignores that rgb box.
Can you point me to some links or give me a general idea how to do this.
Best regards
P.S. image is just a .jpg, the background is white an in the middle there is an item.
UPDATE
This is my code for collecting RGB using impixel
px=impixel(img);
st = num2cell(px,1);
zstup = cellfun(#sum,st);
zred = size(px,1);
rez = bsxfun(#rdivide,zstup,zred);
trez=round(rez);
What I want to do is :
http://imageshack.us/photo/my-images/696/exsample.jpg/
So every box like A1, A2, and so on will return RGB value like trez in my code.
So in my code i save my trez data in a table and it is like in excell lets say 220 | 23 | 34, now if i do that to another fruit i will have
220 | 23 | 34
123 | 212| 78
and so on...
Returning to automatization, A7 and A 15 would not be good RGB canditades because they have more then 50% white area so everything that has 20% white will be ignored.
So A31 is good and the RGB value needs to be saved.
So all in all here i would have my be 6 RGB values that would have to be automatically saved like the above example.
I know how to save to table i just need help for the gathering rgb values in every box.
Depending on your exact needs I see two solutions:
Downscale the image using impyramid(img, 'reduce'). This gives you a smaller image consisting of average values of the original image. Then do what you did before to access single pixels. Repeat as often as necessary to get 2x2, 4x4, 8x8 or larger "boxes".
Or you could use define a box (or arbitrary shape) as a matrix of ones and zeros and use the regionprops function in order to get information about the images content depending on the fields containing ones:
roi = zeros(size(img))
roi(1:10,1:10) = 1;
r = regionprops(roi, img, 'MeanIntensity')
average = r.MeanIntensity
This is my complete code for automatic color grabing from pictures in folder. So the program asks you to chose a folder and after that you get a table full of information about color and roundess. I am using this code to get color from fruits that have white background . It does everything by itself. Hope it helps someone.
clear all;
clc;
uiwait(msgbox('Chose the folder where your pictures are kept. Click OK to continue..'));
% Opening the folder
folder = uigetdir(pwd);
filePattern = fullfile(folder, '*.jpg');
jpegFiles = dir(filePattern);
for k = 1:length(jpegFiles)
baseFileName = jpegFiles(k).name;
fullFileName = fullfile(folder, baseFileName);
[pathstr, name, ext] = fileparts(fullFileName);
naziv_voca=name;
%Taking RGB color
slika = imread(fullFileName);
[redovi stupci RGBboje] = size(slika);
red_ink = floor(redovi/10);
stup_ink = floor(stupci/10);
r = 1;
c = 1;
for stupac = 1 : stup_ink : stupci
for red = 1 : red_ink : redovi
red1 = red;
red2 = red1 + red_ink;
stupac1 = stupac;
stupac2 = stupac1 + stup_ink;
red2 = min(red2, redovi);
stupac2 = min(stupac2, stupci);
crveniS = slika(red1:red2, stupac1:stupac2, 1);
zeleniS = slika(red1:red2, stupac1:stupac2, 2);
plaviS = slika(red1:red2, stupac1:stupac2, 3);
crvena(r,c) = mean2(crveniS);
zelena(r,c) = mean2(zeleniS);
plava(r,c) = mean2(plaviS);
r = r + 1;
if r >redovi
r = 1;
end
end
c = c + 1;
if c >1
c = 1;
end
end
RGB=[crvena,zelena,plava];
bijela=[255 255 255];
tolerancija = 50;
rez = RGB((abs(RGB(:,1)-bijela(1)) > tolerancija) | (abs(RGB(:,2)-bijela(2)) > tolerancija),:);
trez=round(rez);
%Taking shape
pic = rgb2gray(slika);
threshold = graythresh(pic);
bw = im2bw(pic,threshold);
fbw = ones(size(bw))-imfill(ones(size(bw))-bw);
invImg = ~fbw;
f = bwlabel(invImg);
S = regionprops(f,'Area','Perimeter','centroid');
Thr=100;
S=S([S.Area]>Thr);
score = (min(sqrt([S.Area]),[S.Perimeter]/4)./(max(sqrt([S.Area]), [S.Perimeter]/4))).^2;
score=max(score);
%Inserting data into table and creating data
if exist('tablica.mat','file')
vel=size(trez,1);
for z=1:vel
s=load('tablica');
olddata=s.data;
temp=trez(z,:);
dataCell= [naziv_voca,num2cell(temp),num2cell(score)];
data=[olddata;dataCell];
save('tablica.mat','-append','data');
end
else
stupac_rgb = num2cell(trez,1);
zstupac = cellfun(#sum,stupac_rgb);
zred = size(trez,1);
rez = bsxfun(#rdivide,zstupac,zred);
trez=round(rez);
data= [naziv_voca,num2cell(trez),num2cell(score)];
save('tablica','data')
end
end
uiwait(msgbox('Your information is saved'));