I want to make a video for a presentation using Digiflow, converting a .dvi or .dfm file to a .avi. I would like the final image to have a set colour scheme and I would like the time displayed in the corner of the screen.
Use Tools > Transform Intensity. Put the following in the space for Digiflow code.
# Specify output image as a function of P
hD := draw_start(P);
draw_set_axes(hD,0,1,0,1);
draw_font(hD,1,"Arial");
draw_text(hD,0.15,0.03,make_string(Time.tNow,"f5.1")+" s","left");
mask := draw_on_array(hD);
mask := mask.image[:,:,0];
P := where(mask,P,1);
This should put the time in the bottom left of the output image. To change the colour scheme use 'Options' for the output image and save as an .avi to convert.
Related
I'm trying to do simple thing - replace default cursor with my cursor, this is what I'm doing:
I prepared simple 64x64 png image:
Settings from Unity:
What I'm seeing in Game View
I'm setting this cursor through the code using this simple line:
Cursor.SetCursor(CursorTexture, CursorHotspot, CursorMode.Auto);
My goal is to remove just black background and leave star as it is, without making it transparent..
Do you have any idea how to solve this problem ?
The Unity documentation over here says that:
From Gray Scale
This generates the alpha from the mean (average) of the input Texture RGB values.
So the alpha of your image is the average of all of your Texture's RGB values.
Is there a reason you can't simply use a .png image with a transparent background instead?
I'm trying to paste an image onto another, using:
original = Img.open('original.gif')
tile_img = Img.open('tile_image.jpg')
area = 0, 0, 300, 300
original.paste(tile_img, area)
new_cropped.show()
This works except the pasted image changes color to grey.
Image before:
Image after:
Is there a simple way to retain the same pasted image color? I've tried reading the other questions and the documentation, but I can't find any explanation of how to do this.
Many thanks
I believe all GIF images are palettised - that is, rather than containing an RGB triplet at each location, they contain an index into a palette of RGB triplets. This saves space and improves download speed - at the expense of only allowing 256 unique colours per image.
If you want to treat a GIF (or palettised PNG file) as RGB, you need to ensure you convert it to RGB on opening, otherwise you will be working with palette indices rather than RGB triplets.
Try changing the first line to:
original = Img.open('original.gif').convert('RGB')
I have RGB museum JPG Images. most of them have image footnotes on one or more sides, and I'd like to remove them. I do that manually using paint software. now I applied the following matlab code to remove the image footnotes automatically. I get a good result for some images but for others it not remove any border. Please, can any one help me by update this code to apply it for all images?
'rgbIm = im2double(imread('A3.JPG'));
hsv=rgb2hsv(rgbIm);
m = hsv(:,:,2);
foreground = m > 0.06; % value of background
foreground = bwareaopen(foreground, 1000); % or whatever.
labeledImage = bwlabel(foreground);
measurements = regionprops(labeledImage, 'BoundingBox');
ww = measurements.BoundingBox;
croppedImage = imcrop(rgbImage, ww);'
In order to remove the boundaries you could use "imclearborder", where it checks for labelled components at boundaries and clears them. Caution! if the ROI touches the boundary, it may remove. To avoid such instance you can use "imerode" with desired "strel" -( a line or disc) before clearing the borders. The accuracy or generalizing the method to work for all images depends entirely on "threshold" which separates the foreground and background.
More generic method could be - try to extract the properties of footnotes. For instance, If they are just some texts, you can easily remove them by using a edge detection and morphology opening with line structuring element along the cols. (basic property for text detection)
Hope it helps.
I could give you a clear idea or method if you upload the image.
I am processing a group of DICOM images using both ImageJ and Matlab.
In order to do the processing, I need to find spots that have grey levels between 110 and 120 in an 8 bit-depth version of the image.
The thing is: The image that Matlab and ImageJ shows me are different, using the same source file.
I assume that one of them is performing some sort of conversion in the grey levels of it when reading or before displaying. But which one of them?
And in this case, how can I calibrate do so that they display the same image?
The following image shows a comparison of the image read.
In the case of the imageJ, I just opened the application and opened the DICOM image.
In the second case, I used the following MATLAB script:
[image] = dicomread('I1400001');
figure (1)
imshow(image,[]);
title('Original DICOM image');
So which one is changing the original image and if that's the case, how can I modify so that both version looks the same?
It appears that by default ImageJ uses the Window Center and Window Width tags in the DICOM header to perform window and level contrast adjustment on the raw pixel data before displaying it, whereas the MATLAB code is using the full range of data for the display. Taken from the ImageJ User's Guide:
16 Display Range of DICOM Images
With DICOM images, ImageJ sets the
initial display range based on the Window Center (0028, 1050) and
Window Width (0028, 1051) tags. Click Reset on the W&L or B&C window and the display range will be set to the minimum and maximum
pixel values.
So, setting ImageJ to use the full range of pixel values should give you an image to match the one displayed in MATLAB. Alternatively, you could use dicominfo in MATLAB to get those two tag values from the header, then apply window/leveling to the data before displaying it. Your code will probably look something like this (using the formula from the first link above):
img = dicomread('I1400001');
imgInfo = dicominfo('I1400001');
c = double(imgInfo.WindowCenter);
w = double(imgInfo.WindowWidth);
imgScaled = 255.*((double(img)-(c-0.5))/(w-1)+0.5); % Rescale the data
imgScaled = uint8(min(max(imgScaled, 0), 255)); % Clip the edges
Note that 1) double is used to convert to double precision to avoid integer arithmetic, 2) the data is assumed to be unsigned 8-bit integers (which is what the result is converted back to), and 3) I didn't use the variable name image because there is already a function with that name. ;)
A normalized CT image (e.g. after the modality LUT transformation) will have an intensity value ranging from -1024 to position 2000+ in the Hounsfield unit (HU). So, an image processing filter should work within this image data range. On the other hand, a RGB display driver can only display 256 shades of gray. To overcome this limitation, most typical medical viewers apply Window Leveling to create a view of the image where the anatomy of interest has the proper contrast to display in the RGB display driver (mapping the image data of interest to 256 or less shades of gray). One of the ways to define the Window Level settings is to use Window Center (0028,1050) and Window Width (0028,1051) tags. Also, a single CT image can have multiple Window Level values and each pair is basically a view of the anatomy of interest. So using view data for image processing, instead actual image data, may not produce consistent results.
I am working on a 3D DICOM file. After it is read (using MATLAB, for example) I see that it contains some text information apart from the actual scan image. I mean text which is visible in the image when I do implay(), not the header text in the DICOM file. Is there any way by which I can load only the raw data without the text? The text is hindering my processing.
EDIT: I cannot share the image I'm working on due to it being proprietary, but I found the following image after googling:
http://www.microsoft.com/casestudies/resources/Images/4000010832/image7.jpeg http://www.microsoft.com/casestudies/resources/Images/4000010832/image7.jpeg
Notice how the text on the left side partially overlaps the image? There is a similar effect in the image I'm working on. I need just the conical scan image for processing.
As noted, you need to provide more information, as there are a number of ways the overlay can be added: if it's burned into the image, you're generally out of luck; if it's in the overlay plane module (the 60xx tag group), you can probably just remove those prior to passing into Matlab; if it's stored in the unused high bit (an old but common method), you'll have to use the overlay bit position (60xx,0102) to clear out the data in the pixel data.
For the last one, something like the Matlab equivilent of this Java code:
int position = object.getInt( Tag.OverlayBitPosition, 0 );
if( position == 0 ) return;
// Remove the overlay data in high-bit specified.
//
int bit = 1 << position;
int[] pixels = object.getInts( Tag.PixelData );
int count = 0;
for( int pix : pixels )
{
int overlay = pix & bit;
pixels[ count++ ] = pix - overlay;
}
object.putInts( Tag.PixelData, VR.OW, pixels );
If you refer to the text in the blue area on top of the image, these contents are burned into the image itself.
The only solution to remove that is to apply a mask to this area of the image.
Be careful, because doing this is a modification of the original DICOM image. Such kind of modifications are not allowed in some scenarios.