In CImg, I have split an RGBA image apart into multiple single-channel images, with code like:
CImg<unsigned char> input("foo.png");
CImg<unsigned char> r = input.get_channel(0), g = input.get_channel(1), b = input.get_channel(2), a = input.get_channel(3);
Then I try to swizzle the channel order:
CImg<unsigned char> output(input.width(), input.height(), 1, input.channels());
output.channel(0) = g;
output.channel(1) = b;
output.channel(2) = r;
output.channel(3) = a;
When I save the image out, however, it turns out grayscale, apparently based on the alpha channel value; for example, this input:
becomes this output:
How do I specify the image color format so that CImg saves into the correct color space?
Simply copying a channel does not work like that; a better approach is to copy the pixel data with std::copy:
std::copy(g.begin(), g.end(), &output.atX(0, 0, 0, 0));
std::copy(b.begin(), b.end(), &output.atX(0, 0, 0, 1));
std::copy(r.begin(), r.end(), &output.atX(0, 0, 0, 2));
std::copy(a.begin(), a.end(), &output.atX(0, 0, 0, 3));
This results in an output image like:
Related
I have an RGB image which is read as a matrix with 3 dimensions, img, and I have a binary mask which represents a segmentation of the image, mask.
How can I crop the image based on the binary mask in matlab?
I tried to select only the pixels marked by the binary mask but the resulted image does not have the original colors.
centralPoints = find(mask > 0);
denoisedImage = zeros(424, 424, 3);
slice1 = zeros(424, 424);
origSlice = img(:, :, 1);
slice1(centralPoints) = origSlice(centralPoints);
slice2 = zeros(424, 424);
origSlice = img(:, :, 2);
slice2(centralPoints) = origSlice(centralPoints);
slice3 = zeros(424, 424);
origSlice = img(:, :, 3);
slice3(centralPoints) = origSlice(centralPoints);
denoisedImage(:, :, 1) = slice1;
denoisedImage(:, :, 2) = slice2;
denoisedImage(:, :, 3) = slice3;
This is the code. img is the original image, centralPoints are the coordinates of the foreground pixels and denoisedImage represents the cropped matrix.
However, denoisedImage does no maintain the colors of the original image inside the cropped region.
The foreground pixels do not form a rectangular region, however, they form one connected component.
Have you tried
denoisedImage = bsxfun( #times, im2double(img), mask > 0 );
I am new with Image processing in Matlab, I am trying to segment LUNG and nodules from CT image. I have done initial image enhancement.
I searched lot on the same but I haven't found any relevant materials.
Trying to segment lung part from the given image; and then detecting nodules on Lung part.
Code I tried in Matlab:
d1 = dicomread('000000.dcm');
d1ca = imadjust(d1);
d1nF = wiener2(d1ca);
d1Level = graythresh(d1nF);
d1sBW = im2bw(d1nF,d1Level);
sed = strel('diamon',1);
BWfinal = imerode(d1sBW,sed);
BWfinal = imerode(BWfinal,sed);
BWoutline = bwperim(BWfinal);
Segout = d1nF;
Segout(BWoutline) = 0;
edgePrewitt = edge(d1nF,'prewitt');
Result of above code:
Want results like this:
http://oi41.tinypic.com/35me7pj.jpg
http://oi42.tinypic.com/2jbtk6p.jpg
http://oi44.tinypic.com/w0kthe.jpg
http://oi40.tinypic.com/nmfaio.jpg
http://oi41.tinypic.com/2nvdrie.jpg
http://oi43.tinypic.com/2nvdnhk.jpg
I know its may be easy for experts. Please help me out.
Thank you!
The following is not a Matlab answer! However, OpenCV and Matlab share many features in common, and I'm sure you will be able to translate this C++ code to Matlab with no problems.
For more information about the methods being called, check the OpenCV documentation.
#include <iostream>
#include <vector>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
int main(int argc, char* argv[])
{
// Load input image (colored, i.e. 3-channel)
cv::Mat input = cv::imread(argv[1]);
if (input.empty())
{
std::cout << "!!! failed imread()" << std::endl;
return -1;
}
// Convert input image to grayscale (1-channel)
cv::Mat grayscale = input.clone();
cv::cvtColor(input, grayscale, cv::COLOR_BGR2GRAY);
What grayscale looks like:
// Erode & Dilate to remove noises and improve the result of the next operation (threshold)
int erosion_type = cv::MORPH_RECT; // MORPH_RECT, MORPH_CROSS, MORPH_ELLIPSE
int erosion_size = 3;
cv::Mat element = cv::getStructuringElement(erosion_type,
cv::Size(2 * erosion_size + 1, 2 * erosion_size + 1),
cv::Point(erosion_size, erosion_size));
cv::erode(grayscale, grayscale, element);
cv::dilate(grayscale, grayscale, element);
What grayscale looks like after morphological operations:
// Threshold to segment the area of the lungs
cv::Mat thres;
cv::threshold(grayscale, thres, 80, 150, cv::THRESH_BINARY);
What thres looks like:
// Find the contours of the lungs in the thresholded image
std::vector<std::vector<cv::Point> > contours;
cv::findContours(thres, contours, cv::RETR_LIST, cv::CHAIN_APPROX_SIMPLE);
// Fill the areas of the lungs with BLUE for better visualization
cv::Mat lungs = input.clone();
for (size_t i = 0; i < contours.size(); i++)
{
std::vector<cv::Point> cnt = contours[i];
double area = cv::contourArea(cv::Mat(cnt));
if (area > 15000 && area < 35000)
{
std::cout << "* Area: " << area << std::endl;
cv::drawContours(lungs, contours, i, cv::Scalar(255, 0, 0),
CV_FILLED, 8, std::vector<cv::Vec4i>(), 0, cv::Point() );
}
}
What lungs looks like:
// Using the image with blue lungs as a mask, we create a new image containing only the lungs
cv::Mat blue_mask = cv::Mat::zeros(input.size(), CV_8UC1);
cv::inRange(lungs, cv::Scalar(255, 0, 0), cv::Scalar(255, 0, 0), blue_mask);
cv::Mat output;
input.copyTo(output, blue_mask);
What output looks like:
At this point you have the lungs isolated in the image and can proceed to execute other filter operations to isolate the nodules.
Good luck.
Try this:
% dp6BK.png is your original image, I downloaded directly
I = im2double(imread('dp6BK.png'));
I=I(:,:,1);
imshow(I)
cropped = I(50:430,8:500); %% Crop region of interest
thresholded = cropped < 0.35; %% Threshold to isolate lungs
clearThresh = imclearborder(thresholded); %% Remove border artifacts in image
Liver = bwareaopen(clearThresh,100); %% Remove objects less than 100 pixels
Liver1 = imfill(Liver,'hole'); % fill in the vessels inside the lungs
figure,imshow(Liver1.*cropped)
What you will get:
So I need to take an image I made in PIL and convert it to a pixmap to be displayed in a drawable.
How do I convert from PIL to pixmap and keep the images alpha?
Currently I have this code written:
def gfx_draw_tem2(self, r, x, y):
#im = Image.open("TEM/TEM cropped.png")
im = Image.new("RGBA", (r*2,r*2), (255, 255, 255, 255))
draw = ImageDraw.Draw(im)
for i in range(0,r*2):
for j in range(0,r*2):
if(self.in_circle(i,j,r)):
draw.point((i,j), fill=(100,50,75,50)) #alpha at 255 for test2.png
im.save("test.png")
im_data = im.tostring()
pixbuf = gdk.pixbuf_new_from_data(im_data, gdk.COLORSPACE_RGB, True, 8, im.size[0], im.size[1], 4*im.size[0])
pixmap2, mask = pixbuf.render_pixmap_and_mask()
self.pixmap.draw_drawable(self.white_gc, pixmap2, 0,0,x-r,y-r,-1,-1)
Here are the images I created from im.save("test.png"):
http://imgur.com/43spsBG,lqowten#0
Notice the first picture has an alpha of 255 (full) and the seconds has an alpha of 50.
However When I convert the images to a pixmap with my current code I lose the transparent affect.
Thanks for your help,
Ian
EDIT: I have narrowed it down a little bit with more testing. I am losing the alpha of my image when converting the pixbuf to a pixmap.
Okay figured it out.
Trick here is to not convert the pixbuf to a pixmap using pixbuf.render_pixmap_and_mask()
Instead I took my self.pixmap that I draw onto my drawable and called draw_pixbuf() on it.
Here is the new code I used.
def gfx_draw_tem2(self, r, x, y):
im = Image.new("RGBA", (r*2,r*2), (1, 1, 1, 0))
draw = ImageDraw.Draw(im)
for i in range(0,r*2):
for j in range(0,r*2):
if(self.in_circle(i,j,r)):
draw.point((i,j), fill=(100,50,75,140))
im_data = im.tostring()
pixbuf = gdk.pixbuf_new_from_data(im_data, gdk.COLORSPACE_RGB, True, 8, im.size[0], im.size[1], 4*im.size[0])
self.pixmap.draw_pixbuf(self.white_gc, pixbuf, 0, 0, x, y, -1, -1, gdk.RGB_DITHER_NORMAL, 0, 0)
Hope this helps someone.
Basically i want to implement color replacement feature for my paint application.
Below are original and expected output
Original:
After changing wall color selected by user along with some threshold for replacement
I have tried two approaches but could not got working as expected
Approach 1:
Queue-based Flood Fill algorithm for color replacement
but with i got below output with terribly slow and wall shadow has not been preserved.
Approach 2:
So i have tried to look at another option and found below post from SO
How to change a particular color in an image?
but i could not understand logic and not sure about my code implementation from step 3.
Please find below code for each step wise with my understanding.
1) Convert the image from RGB to HSV using cvCvtColor (we only want to
change the hue).
IplImage *mainImage=[self CreateIplImageFromUIImage:[UIImage imageNamed:#"original.jpg"]];
IplImage *hsvImage = cvCreateImage(cvGetSize(mainImage), IPL_DEPTH_8U, 3);
IplImage *threshImage = cvCreateImage(cvGetSize(mainImage), IPL_DEPTH_8U, 3);
cvCvtColor(mainImage,hsvImage,CV_RGB2HSV);
2) Isolate a color with cvThreshold specifying a
certain tolerance (you want a range of colors, not one flat color).
cvThreshold(hsvImage, threshImage, 0, 100, CV_THRESH_BINARY);
3) Discard areas of color below a minimum size using a blob detection
library like cvBlobsLib. This will get rid of dots of the similar
color in the scene. Do i need to specify original image or thresold image?
CBlobResult blobs = CBlobResult(threshImage, NULL, 0);
blobs.Filter( blobs, B_EXCLUDE, CBlobGetArea(), B_LESS, 10);
4) Mask the color with cvInRangeS and use the
resulting mask to apply the new hue.
Not sure about this function how it helps in color replacement and not able to understand arguments to be provided.
5) cvMerge the new image with the
new hue with an image composed by the saturation and brightness
channels that you saved in step one.
i understand that cvMerge will merge three channel of H S and V but how i can use output of above three steps.
so basically stuck with opencv implementation,
if possible then please guide me for opencv implemenation or any other solution to tryout.
Finally i am able to achieve some desired output using below javacv code and same ported to opencv too.
this solution has 2 problems
don't have edge detection, i think using contours i can achieve it
replaced color has flat hue and sat which should set based on source
pixel hue sat difference but not sure how to achieve that. may be
instead of cvSet using cvAddS
IplImage image = cvLoadImage("sample.png");
CvSize cvSize = cvGetSize(image);
IplImage hsvImage = cvCreateImage(cvSize, image.depth(),image.nChannels());
IplImage hChannel = cvCreateImage(cvSize, image.depth(), 1);
IplImage sChannel = cvCreateImage(cvSize, image.depth(), 1);
IplImage vChannel = cvCreateImage(cvSize, image.depth(), 1);
cvSplit(hsvImage, hChannel, sChannel, vChannel, null);
IplImage cvInRange = cvCreateImage(cvSize, image.depth(), 1);
CvScalar source=new CvScalar(72/2,0.07*255,66,0); //source color to replace
CvScalar from=getScaler(source,false);
CvScalar to=getScaler(source, true);
cvInRangeS(hsvImage, from , to, cvInRange);
IplImage dest = cvCreateImage(cvSize, image.depth(), image.nChannels());
IplImage temp = cvCreateImage(cvSize, IPL_DEPTH_8U, 2);
cvMerge(hChannel, sChannel, null, null, temp);
cvSet(temp, new CvScalar(45,255,0,0), cvInRange);// destination hue and sat
cvSplit(temp, hChannel, sChannel, null, null);
cvMerge(hChannel, sChannel, vChannel, null, dest);
cvCvtColor(dest, dest, CV_HSV2BGR);
cvSaveImage("output.png", dest);
method to for calculating threshold
CvScalar getScaler(CvScalar seed,boolean plus){
if(plus){
return CV_RGB(seed.red()+(seed.red()*thresold),seed.green()+(seed.green()*thresold),seed.blue()+(seed.blue()*thresold));
}else{
return CV_RGB(seed.red()-(seed.red()*thresold),seed.green()-(seed.green()*thresold),seed.blue()-(seed.blue()*thresold));
}
}
I know this answer will be useful to someone someday.
try this out in your view viewdidLoad() override method for iOS.
image in the code snippet below should be from your UIImageView
seed also is fixed.you can make it dynamic based on user tap event.
cv::Mat mask = cv::Mat::zeros(image.rows + 2, image.cols + 2, CV_8U);
imageView.image = [self UIImageFromCVMat:image];
cv::cvtColor(image, image, cv::COLOR_BGR2RGB);
try {
if(seed.x > 0 && seed.y > 0){
cv::floodFill(image, mask, seed, cv::Scalar(50, 155, 20) ,0, cv::Scalar(2,2, 2), cv::Scalar(2,2, 2), 8);
cv::floodFill(image, mask, seed2, cv::Scalar(50, 155, 20) ,0, cv::Scalar(2,2, 2), cv::Scalar(2,2, 2), 8);
cv::floodFill(image, mask, seed3, cv::Scalar(50, 155, 0) ,0, cv::Scalar(2,2, 2), cv::Scalar(2,2, 2), 8);
}
} catch (Exception ex) {
}
cv::cvtColor(image, image, cv::COLOR_RGB2BGR);
self.imageView.contentMode = UIViewContentModeScaleAspectFill;
self.imageView.image = [self UIImageFromCVMat:image];
I have got the picture that has got a text in it. I have already converted that picture into grayscale by using the ColorMatrix.
public Bitmap MakeGrayscale(Bitmap original)
{
//create a blank bitmap the same size as original
Bitmap newBitmap = new Bitmap(original.Width, original.Height);
//get a graphics object from the new image
Graphics g = Graphics.FromImage(newBitmap);
//create the grayscale ColorMatrix
ColorMatrix colorMatrix = new ColorMatrix(
new float[][]
{
new float[] {.3f, .3f, .3f, 0, 0}, // 30% red.
new float[] {.59f, .59f, .59f, 0, 0}, // 59% green.
new float[] {.11f, .11f, .11f, 0, 0}, // 11% blue.
new float[] {0, 0, 0, 1, 0},
new float[] {0, 0, 0, 0, 1}
});
//create some image attributes
ImageAttributes attributes = new ImageAttributes();
//set the color matrix attribute
attributes.SetColorMatrix(colorMatrix);
//draw the original image on the new image
//using the grayscale color matrix
g.DrawImage(original, new Rectangle(0, 0, original.Width, original.Height),
0, 0, original.Width, original.Height, GraphicsUnit.Pixel, attributes);
//dispose the Graphics object
g.Dispose();
return newBitmap;
}
Now, this is a fairly grayscale (black and white tone). I want to increase the black tone and make darker which I could do with Photoshop. Please let me know how can I achieve this in C#?
Please let me know.
Cheers! :)
One way is the generally enforce the pixels to be darker, try iterating over all pixels (Color objects) in the Bitmap, and replace them with new colors which are darker by a percentage
This snippet might help
/// <summary>
/// Darkens the immage, giving a number greater then one will not brighten the image correctly
/// </summary>
/// <param name="bmp">The bitmap to darken</param>
/// <param name="multiplier">The multiplier, should be less then oen to darker the picture</param>
static void DarkenImage(Bitmap bmp, double multiplier)
{
for (int i = 0; i < bmp.Width; i++)
{
// Iterates over all the pixels
for (int j = 0; j < bmp.Height; j++)
{
// Gets the current pixel
var currentPixel = bmp.GetPixel(i, j);
// Assigns each value the multiply, or the max value 255
var newPixel = Color.FromArgb(
Math.Min((byte)255, (byte)(currentPixel.R * multiplier)),
Math.Min((byte)255, (byte)(currentPixel.G * multiplier)),
Math.Min((byte)255, (byte)(currentPixel.B * multiplier))
);
// Sets the pixel
bmp.SetPixel(i, j, newPixel);
}
}
}