I'm reading a dicom image and accessing its pixel array. After that saving that array again into dicom format using sitk.Write but there is different between original image that is going to be read and same image after being written. How can I get the same image display. I'm using Radiant Viewer for visualization of Dicom images. I want same output as of input. Code along with input and out image is given below:
# Reading a dicom image
Image = pydicom.dcmread('Input.dcm')
output = Image.pixel_array
#Saving the image into another folder
img = sitk.GetImageFromArray(output)
sitk.WriteImage(img, 'output.dcm' )
Size of dicom image is greater so sending the screenshots of input1 and output2 image
I'm gonna answer my own question here. So, the Photometric Interpretation of my original image was MONOCHROME1. But after converting the image into pixel arrays and then saving again with .dcm format, its some details were changed one of which was Photometric Interpretation that changed from MONOCHROME1 to MONOCHROME2. I changed this of the saved image and then saved again as follows.
elem = image[0x0028, 0x0004]
elem.value = 'MONOCHROME1'
image.save_as('P1_L_CC.dcm',write_like_original=False)
Related
Source Image
enter image description here
covert into excle
enter image description here
Current i am doing slicing but it taking too much time not accurate
enter image description here
I am new to machine learning.
I want to prepare a document with a signature at the bottom of it.
For this purpose I am taking a photo of the user's signature for placement in the document.
How can I using machine learning extract only the signature part from the image and place it on the document?
Input example:
Output expected in gif format:
Extract the green image plane. Then take the complementary of the gray value of every pixel as the transparency coefficient. Then you can perform compositing to the destination.
https://en.wikipedia.org/wiki/Alpha_compositing
A simple image-processing technique using OpenCV should work. The idea is to obtain a binary image then bitwise-and the image to remove the non-signature details. Here's the results:
Input image
Binary image
Result
Code
import cv2
# Load image, convert to grayscale, Gaussian blur, Otsu's threshold
image = cv2.imread('1.jpg')
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
blur = cv2.GaussianBlur(gray, (3,3), 0)
thresh = cv2.threshold(blur, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]
# Bitwise-and and color background white
result = cv2.bitwise_and(image, image, mask=thresh)
result[thresh==0] = [255,255,255]
cv2.imshow('thresh', thresh)
cv2.imshow('result', result)
cv2.waitKey()
Please do research before posting questions like these. A simple google search of "extract signature from image python" gave so many results.
Git Repo
Git Repo
Stack Overflow
There are many other such alternatives. Please have a look and try a few approaches.
If you still have some questions or doubts, then post the approach you have taken and a discussion is warranted.
I am using PDFBox 2.0.8 to replace image in my application. I am able to extract the image and replace the same with another image of same dimension. However, there is no decrease in the size of PDF if there is decrease in the size of image. For example refer the documents/images in the below links. Original size of PDF is 93 KB. Extracted image is 91 KB. Replaced image is 54 KB. PDF size after image replacement is still 92 KB....
Original Document = http://35.200.192.44/download?fileName=/outbox/pdf/10_cert.pdf
Extracted Image = http://35.200.192.44/download?fileName=/outbox/pdf/image0.jpg
Replacement image = http://35.200.192.44/download?fileName=/outbox/pdf/image1.jpg
PDF after replacement = http://35.200.192.44/download?fileName=/outbox/pdf/10_cert1.pdf.
The change in size of PDF after replacement is not in the same proportion... Code snippet used for image replacement is
BufferedImage buffered_replacement_image_file = ImageIO.read(new File(replacement_image_file));
PDImageXObject replacement_img = JPEGFactory.createFromImage(doc, buffered_replacement_image_file);
resources.put(xObjectName, replacement_img);
The images in your two example PDFs are identical. This most likely is due to the way you load the image data, first creating a BufferedImage from the file and then creating a PDImageXObject from that BufferedImage. This causes the input image data to be expanded to a plain bitmap and then re-compressed to JPEG identically by JPEGFactory.createFromImage.
To use the JPEG data as they initially are, try this approach instead:
PDImageXObject replacement_img = JPEGFactory.createFromStream(doc, new FileInputStream(replacement_image_file));
resources.put(xObjectName, replacement_img);
or, if the replacement_image_file is not necessarily a JPEG file, like this
PDImageXObject replacement_img = PDImageXObject.createFromFileByExtension(new File(replacement_image_file), doc);
resources.put(xObjectName, replacement_img);
If this doesn't help, you most likely have other issues in your code, too, and need to show more of it.
I want to composite a number of images into a single window in openCV. I had found i could create a ROI in one image and copy another colour image into this area without any problems.
Switching the source image to an image i had carried out some processing on didn't work though.
Eventually i found out that i'd converted the src image to greyscale and that when using the copyTo method that it didn't copy anything over.
I've answered this question with my basic solution that only caters for greyscale to colour. If you use other Mat image types then you'd have to carry out the additional tests and conversions.
I realised my problem was i was trying to copy a greyscale image into a colour image. As such i had to convert it into the appropriate type first.
drawIntoArea(Mat &src, Mat &dst, int x, int y, int width, int height)
{
Mat scaledSrc;
// Destination image for the converted src image.
Mat convertedSrc(src.rows,src.cols,CV_8UC3, Scalar(0,0,255));
// Convert the src image into the correct destination image type
// Could also use MixChannels here.
// Expand to support range of image source types.
if (src.type() != dst.type())
{
cvtColor(src, convertedSrc, CV_GRAY2RGB);
}else{
src.copyTo(convertedSrc);
}
// Resize the converted source image to the desired target width.
resize(convertedSrc, scaledSrc,Size(width,height),1,1,INTER_AREA);
// create a region of interest in the destination image to copy the newly sized and converted source image into.
Mat ROI = dst(Rect(x, y, scaledSrc.cols, scaledSrc.rows));
scaledSrc.copyTo(ROI);
}
Took me a while to realise the image source types were different, i'd forgotten i'd converted the images to grey scale for some other processing steps.
• Background :
We are developing AFP to PDF tool. It involves conversion of AFP (Advanced Function Processing) file to PDF.
• Detailed Problem statement :
We have AFP file with embedded TIFF Image. The image object is described in Function Set 45, represented somewhat like this -
Image Content
Begin Tile
Image Encoding Parameter – TIFF LZW
Begin Transparency Mask
Image Encoding Parameter – G4MMR
Image Data Elements
End Transparency Mask
Image Data Elements (IDE Size 32) – 4 bands: CMYK
End Tile
End Image Content
We want to write this tiled image to PDF either using Java /iText API.
As of now, we can write G4MMR image. But, we are not able to apply CMYK color band data (Blue Color) to this image.
• Solution tried :
The code to write G4MMR image goes as follows –
ByteArrayOutputStream decode = saveAsTIFF(<width>,<height>,<imageByteData>);
RandomAccessFileOrArray ra=new RandomAccessFileOrArray(saveAsTIFF.toByteArray());
int pages = TiffImage.getNumberOfPages(ra);
for(int i1 = 1; i1 <= pages; i1++){
img1 = TiffImage.getTiffImage(ra, i1);
}
img1.scaleAbsolute(256, 75);
document.add(img1);
saveAsTIFF method is given here –
http://www.jpedal.org/PDFblog/2011/08/ccitt-encoding-in-pdf-files-converting-pdf-ccitt-data-into-a-tiff/
As mentioned, we are not able to apply CMYK 4 band image color data to this G4MMR image.
• Technology stack with versions of each component :
1. JDK 1.6
2. itextpdf-5.1
-- Umesh Pathak
The AFP resource you're showing is a TIFF CMYK image compressed with LZW. This image is also using a "transparency mask" which is compressed with G4MMR ( a slightly different encoding than the traditional Fax style G4).
So the image data is already using the CMYK colorspace, each band (C,M,Y,K) is compressed alone using simple LZW encoding and should not be too difficult to extract and store as a basic TIFF CMYK file. You'll also have to convert the transparency mask to G4 or raw data to use it in a pdf file to maks the CMYK image.
If you want better PDF output control, I suggest you take a look at pdflib
You need to add a CMYK colorspace to your image before adding it to the PDF file. However I am afraid this might not be fully supported in iText. A workaround for you could be to convert your image into the default RGB colorspace before adding it to the PDF file, however this will probably imply some quality loss for your image.