I have this image:
I want to convert this to black and white at small increments, the strange thing is that it just disappears after one increment.
For this line
bw_normal = im2bw(img, 0.33);
I get this:
But for this line:
bw_normal = im2bw(img, 0.32);
The word disappears entirely, this shouldn't happen right? It only happens with this image, any other image will continue to show up until 0.1.
This is what I get at 0.32
Just a white space, can anyone please explain this.
im2bw converts the image to a binary (black/white) image. It does this by comparing all pixels' luminance component to the threshold value you provide as the second argument. If the pixel is brigther, it is made white, if it's darker, it is made black.
In your case, the image has only one color (pretty much). This color has a luminance component between 0.32 and 0.33, so if you use 0.33 as threshold, most of the colored portion of the image will be below the threshold and be made black. If you use 0.32, however, most if not all of the image will be above the threshold and thus be made white.
What you experience is expected behavior since your image is basically white background and a single color for the foreground. Once your "increment" reaches that color's luminance, your image is gone.
Related
I have a problem with some dicom images. Maybe they have a different image range.
Generally it display as normal with black background but sometimes it display with white background. I have a question : what can I change it ? I would like to display images always with black background.
I would appreciate for any help/advice. I don't know what I should change ?
Agata
Please check the value of Photometric Interpretation (0028, 0004). This specifies the intended interpretation of the image pixel data. If the value is “MONOCHROME1” than the minimum sample value of pixel data is intended to be displayed as white (after any Modality LUT transformation) and maximum pixel value as black (inverted grayscale image)
I am working on replacing certain color in image by User's selected color. I am using OpenCV for color replacement.
Here in short I have described from where I took help and what I got.
How to change a particular color in an image?
I have followed the step or taken basic idea from answer of above link. In correct answer of that link that guy told you only need to change hue for colour replacement.
after that I run into the issue similar like
color replacement in image for iphone application (i.e. It's good code for color replacement for those who are completely beginners)
from that issue I got the idea that I also need to change "Saturation" also.
Now I am running into issues like
"When my source image is too light(i.e. with high brightness) and I am replacing colour with some dark colour then colours looks light in replaced image instead of dark due to that it seems like Replaced colour does not match with colour using that we done replacement"
This happens because I am not considering the brightness in replacement. Here I am stuck what is the formula or idea to change brightness?
Suppose I am replacing the brightness of image with brightness of destination colour then It would look like flat replacemnt and image will lose it's actual shadow or edges.
Edit:
When I am considering the brightness of source(i.e. the pixel to be processed) in replacment then I am facing one issue. let me explain as per scenario of my application.
for example I am changing the colour of car(like whiteAngl explain) after that I am erasing few portion of the newly coloured car. Again I am doing recolour on erased portion but now what happended is colour done after erase and colour before erase doesn't match because both time I am getting different lightness because both time my pixel of to be processed is changed and due to that lightness of colour changed in output. How to overcome this issue
Any help will be appreciated
Without seeing the code you have tried, it's not easy to guess what you have done wrong. To show you with a concrete example how this is done let's change the ugly blue color of this car:
This short python script shows how we can change the color using the HSV color space:
import cv2
orig = cv2.imread("original.jpg")
hsv = cv2.cvtColor(orig, cv2.COLOR_BGR2HSV)
hsv[:,:,0] += 100
bgr = cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR)
cv2.imwrite('changed.jpg', bgr)
and you get:
On wikipedia you see the hue is between 0 to 360 degrees but for the values in OpenCV see the documentation. You see I added 100 to hue of every pixel in the image. I guess you want to change the color of a portion of your image, but probably you get the idea from the above script.
Here is how to get the requested dark red car. First we get the red one:
The dark red one that I tried to keep the metallic feeling in it:
As I said, the equation you use to shift the light of the color depends on the material you want to have for the object. Here I came up with a quick and dirty equation to keep the metallic material of the car. This script produces the above dark red car image from the first light blue car image:
import cv2
orig = cv2.imread("original.jpg")
hls = cv2.cvtColor(orig, cv2.COLOR_BGR2HLS)
hls[:,:,0] += 80 # change color from blue to red, hue
for i in range(1,50): # 50 times reduce lightness
# select indices where lightness is greater than 0 (black) and less than very bright
# 220-i*2 is there to reduce lightness of bright pixel fewer number of times (than 50 times),
# so in the first iteration we don't reduce lightness of pixels which have lightness >= 200, in the second iteration we don't touch pixels with lightness >= 198 and so on
ind = (hls[:,:,1] > 0) & (hls[:,:,1] < (220-i*2))
# from the lightness of the selected pixels we subtract 1, using trick true=1 false=0
# so the selected pixels get darker
hls[:,:,1] -= ind
bgr = cv2.cvtColor(hls, cv2.COLOR_HLS2BGR)
cv2.imwrite('changed.jpg', bgr)
You are right : changing only the hue will not change the brightness at all (or very weakly due to some perceptual effects), and what you want is to change the brightness as well. And as you mentioned, setting the brightness to the target brightness will loose all pixel values (you will only see changes in saturation). So what's next ?
What you can do is to change the pixel's hue plus try to match the average lightness. To do that, just compute the average brightness B of all your pixels to be processed, and then multiply all your brightness values by Bt/B where Bt is the brightness of your target color.
Doing that will both match the hue (due to the first step) and the brightness due to the second step, while preserving the edges (because you only modified the average brightness).
This is a special case of histogram matching, where here, your target histogram has a single value (the target color) so only the mean can be matched in a reasonable way.
And if you're looking for a "credible source" as stated in your bounty request, I am a postdoc at Harvard and will be presenting a paper on color histogram matching at Siggraph this year ;) .
This appears to be a trivial problem but the result is strange, totally lost where I am going wrong. There is an input RGB image which needs to be converted to gray scale and sized to 1000 x 1000 pixels. This is how I have done
img=imread('flowers.jpg');
flowers_gray=rgb2gray(img);
flowers_resize=imresize(flowers_gray,[1000 1000]);
but strangely the output image is not of 1000 by 1000 pixels. Moreover, matlab did not save the image (tried using SaveAs option and the File --->Export Setup) gray scale mode
and also the size was incorrect since when I opened the saved image by
img1=imread('flowers_resize.jpg')
s=size(img1)
it gave
s=586 665 3
And the image flowers_resize.jpg is saved with a white border surrounding it in the image folder. So, I went to Paint toolbox to select the image A1 and manually deleted the surrounding background and resized the image.But alas, it saved the image with 3 color channels and not in gray scale mode although the size was correct! Can somebody please point out the correct way of resizing to 1000 by 1000 pixels and saving in gray scale mode without the white border surrounding the saved output file? Thank you.
When you use the image export processing, you are saving the entire figure including the space around the figure (white space).
Instead, use the imwrite command. In your case:
imwrite(A1,'flowers_resize.jpg','jpg');
I'm working with this excellent example of converting an image to grayscale: Convert Image to B&W problem CGContext - iPhone Dev
However, for my purposes, I would like to have only pure black and pure white left in the image.
It appears that to do so, I need to pass a black and white color space to the recolor method using a call:
CGColorSpaceRef colorSpace = CGColorSpaceCreateWithName(/*black and white name*/);
However, I was unable to find the proper iOS color space names. What I found was from Mac, and the "color space names" referenced from the iOS docs does not point anywhere.
How can I properly create a black and white CGColorSpaceRef?
Thank you!
I am not familiar with a black and white only color space but what you can do is calculate the total average RGB value from all the pixels (lets call it totalAvg) and use it as a threshold. Meaning for each pixel if its rgb average is greater than the calculated totalAvg than set it to pure white, otherwise set it to pure black.
I agree it is a bit of more work but thats whay I can think of unless you find the colorspace you are looking for.
You might try creating a gray color space, then creating an indexed color space with two colors (black and white, obviously) and using that.
I've converted a colored photo to black and white, and bolded the edges. Now i need to convert it back to its original color with the bolded edges. Is there any function in matlab which allows me to do so?
Once you remove the colour from an image, there is no possible way to automatically put it back. You're basically reducing a set of 16,777,216 colours to a set of 256 - on average each shade of grey has 65,536 equivalent colours, and without the original image there's no way to guess which it could be.
Now, if you were to take the bolded lines from your black-and-white image and paint them on top of the original coloured image, that might end up producing what you're looking for.
If what you are trying to do is to use some filter over the B/W image and then use that with the original color. I suggest you convert your image to a color space with Lightness channel that suits your needs (for example L*a*b* if you need the ligtness to be uniformly distributed regarding human recognition of differences) and apply your filter only over the Lightness channel.