I have an image that is essentially a text document (black and white) but due to anti-aliasing/undersampling applied during scanning, the image contains a lot of color, light tone pixels and is thus saved as a full-color image i.e: takes a lot of space.
My goal is to be able to detect Black and White image candidates in order to convert them from full color to B&W which dramatically reduces their size.
Is there a way to detect such anti-aliased/undersampled images? Doing color pixel analysis doesn't help because the colored pixels end up being close in amount to the black pixels... Essentially I want to be able to detect that the colored pixels come from anti-aliasing/undersampling a black & white image and not from a picture type image.
Here is an example image:
As you can see there are many more colors than just black. However this image is a good candidate for Black & White / Greyscale conversion instead of full color. How can I detect such images? Please note that in this example the colors tend to be on the grey side but there are many cases where they are cyan or brown etc.
I think it is a valid question. I don't have 50 reputation to post a comment so I will post this as an answer.
Basically, in a black and white anti-aliased image the various grey colors are opacity differences of the black color. If we observe those pixels they will be like these listed below. So, if the operation is a color manipulation then apply the same opacity picked up from those grey pixels to the new color.
rgba(0,0,0,0.6)
rgba(0,0,0,0.9)
rgba(0,0,0,0.5)
rgba(0,0,0,0.9)
rgba(0,0,0,0.6)
rgba(0,0,0,0.1)
rgba(0,0,0,0.5)
In my opinion, the pixels other than grey, in this example image, cyan and brown as it appears can be safely ignored because they seemed like not part of the original text. If there were a few more example images of non grey pixels would have been good. But if we cannot ignore them just need to get the pixel opacity and apply the same color manipulation. In other words we treat them as black pixels.
Related
i am working on a project where i need to do some image processing, where i am not an expert.
I have an image obtained from QEMSCAN technology,as you can see here pink pixels represent the existence of the gold. there are 3 types of gold, type 1 where the connected pink pixels are surrounded with white ones. type 2 when the connected pink pixels are surrounded with white and another color.
type 3 where the pink area is connected with another colors except white.
I did some morphological image processing to isolate each area containing gold, but I'm blocked right now how i can determine to which type belong each pink area
thanks in advance
determine the type of gold
image
Here's a possible approach:
make all the pink pixels white and everything else black
do a dilation and find the coordinates of the additional pixels
check the colour(s) of the additional pixels in the original image
How to change a Golang image.Image's white background to transparent?
I want to put the white background into a translucent color, do you have any suggestions?
This is not possible in general but there are heuristic approaches to attempt this.
Why is it not possible?
If the original image had some transparent pixels and was rendered on a plain white background (or any known background) then in the resulting image there is lost information. For example, is a pink pixel created from a red pixel with some transparency or a truly pink pixel without transparency?
Even a pure white pixel may have been fully white originally, or fully transparent, or somewhere in between.
Heuristic approaches
If you know something about the original image or can infer something by looking at it you may be able to deduce what colour and transparency of the original pixels was. A simple first step is that if the outside pixels are white then you might want to flood fill this area with fully transparent pixels. Also white areas inside coloured areas may be holes that can also be transparent.
Next you can infer the colours of border pixels around objects of a single colour (assuming transparency was used for anti-aliasing). For example for a red circle with pink pixels on the circumference it's likely they were originally red with some transparency leading them to be rendered in different shades of pink. For more complex, multi-coloured shapes you can get a reasonable result by manually editing the image using judgement, knowledge/guesswork of the original image and knowledge of how anti-aliasing was performed.
I wrote a Paint.Net plugin (C#) to automate this sort of thing many years ago and sometimes it gave reasonable results, but often you need to do it by hand.
package "image" has Decode function
func Decode(r io.Reader) (Image, string, error)
image.Image is interface
type Image interface {
// ColorModel returns the Image's color model.
ColorModel() color.Model
// Bounds returns the domain for which At can return non-zero color.
// The bounds do not necessarily contain the point (0, 0).
Bounds() Rectangle
// At returns the color of the pixel at (x, y).
// At(Bounds().Min.X, Bounds().Min.Y) returns the upper-left pixel of the grid.
// At(Bounds().Max.X-1, Bounds().Max.Y-1) returns the lower-right one.
At(x, y int) color.Color
}
after you decode you file into image.Image, you can get Height and Width from Bounds(),and color from At(x,y).
So, here is what to do next:
make another image with alpha channel,
Iterate throw whole image one pix by another,
check color, copy color to new image after you do whatever you want.
I'm trying to implement flood fill method for raster image.
For center pixels it's easy and works correct, but the problem is to fill pixels near border, which have different color.
For example, if draw Black figure on White background, some border pixels will have kind of gray color instead of black (for smoothing).
Image editors (like paint.net) during floodfill fixes it changing these pixels to some middle color between old and new one. Here I filled figure in red color, and gray pixels became in red gradient
I need to know method or algorithm how gray pixels became in kind of color to fill (here it's red, but can be any) using RGB pixel manipulation.
Thanks for any help.
So, for similar effect like in example we just need to use & operation between old and new color.
For RGB color:
resultColor.R = (byte)(oldColor.R & newColor.R);
resultColor.G = (byte)(oldColor.G & newColor.G);
resultColor.B = (byte)(oldColor.B & newColor.B);
If RGB color is Int number:
resultColor = oldColor & newColor;
It will not be exactly same color as in example below but pretty similar.
Using GIMP 2, I have an image of a grey chair on a white background, as below:
I now want to set the background to transparent. Therefore, I decided to use GIMP's "Color To Alpha" tool. So, I told it to set all pixels which are white (255, 255, 255) to transparent, as below:
This did set all white pixels to transparent. However, it also set the grey pixels on the chair to be partially transparent, as below:
So when I export this image and place it in front of a background, there is no white box around the chair -- but the background partially shows through the chair.
What am I doing wrong?
First, this question is offtopic here, and should be on https://graphicdesign.stackexchange.com .
Second, it is trivial enough just to answer: the color to alpha plug-in is not there to turn a single color, as seem on the image, to transparency: it is a sophisticated plug-in that will remove one color of your image in a way that, if you lace the new image over a background of the same color the color you removed, you get the original image back.
Thus, in your case, it removed the "whiteness" of your chair, transforming all pixels to different opaque shades of black - so that when placed over white, you get the original image.
To simply remove the white, you have to cick on the Select By Color tool (by default th 5th icon on the toolbox), click on the white background to have it selected, and then just edit->cut. (It won't work if your image layer does not have transparency to start with - if that is the case, prior to edit->cut do Layer->Transparency->Add Alpha Channel).
If you get aliased borders, then, after edit>cut, but prior to dismissing your selection, you can do Select->Border... by 1 or 2px, and then use the color to alpha filter with White on this selection.
For more information on Color to Alpha, I have this other answer its use and comparison with edit-cut here: https://graphicdesign.stackexchange.com/questions/28058/gimp-color-to-alpha-is-not-selectable/28097#28097
Just use a selection to restrict the action of Color to alpha where it matters: backgroundand edge pixels:
Select background with fuzzy select
Select>Grow by one pixel so that the selection ofverlaps the edge pixels
Color>Color to alpha
I wanna to color a sprite/icon with a transparent background and with shadows. I tried to shift the hue to all pixels but it looks not so natural and I have problems with the black and the white colors in an image. If an image tend to be black shifting the hue do not change the black in red or another color even shifting by 360 degrees.
Tried to color addicting and subtracting color and even in that case the black and the white tend to be colored or disappears at all.
Maybe should I put an image on the icon to achieve the coloring effect ?
Any suggestions on how to proceed.
I lost.
You've been asking a lot about this hue shifting thing, so I figured I'd try to work out an example: http://jsfiddle.net/EMujN/3/
Here's another that uses an actual icon: http://jsfiddle.net/EMujN/4/
There's a lot in there. There's a huge data URL which you can ignore unless you want to replace it. Here's the relevant part where we modify HSL.
//SHIFT H HERE
var hMod = .3;
hsl[0]=(hsl[0]+hMod)%1;
//MODIFY S HERE
var sMod = .6;
hsl[1]=Math.max(0,Math.min(1,
hsl[1]+sMod
));
//MODIFY L HERE
var lMod = 0;
hsl[2]=Math.max(0,Math.min(1,
hsl[2]+lMod
));
I've converted to HSL because it's a lot easier to accomplish what you want in that color space than RGB.
Without getting any more complex, you have three variables you can tune: how much to add to either Hue, Saturation, or Lightness. I have the lightness variable set to 0 because any higher and you will see some nasty JPEG artifacts (if you can find a decent .png that would be better, but I went with the first CC night image I could find).
I think the hue shift (yellow to green) looks pretty good though and I have maxed out the saturation, so even a normally white light appears bright purple. Like I said in my comment, you will need to increase the lightness and saturation if you want to colorize patches of black and white. Hopefully, you can figure out what you need from this example.
image used: http://commons.wikimedia.org/wiki/File:Amman_(Jordan)_at_night.jpg
I found a better solution by myself which can solve the problem with the black and white.
So basically the solution can be solved in multiple steps. Here I will define the steps. Later I'll provide some working code:
Get the image
Calculate the predominant color, averaging the image pixels or simply providing an input RGB value which is the predominant that your eye can catch.
If the predominant tends to be black or white, or both, the image has to be recolored with an addictive or subtractive method, addictive if black, subtractive if white. So basically all RGB pixels should be attenuated or sharpened until RED. I think that the best solution should be RED, because RED is first in the HUE scale, and this can help when we will hue-shift the pixels.
To have a unique algorithm which can work with different kind of images, not only black predominant or white, ideally the input the non-black and non-white predominant images should be pre-hueshifted manually, using photoshop or with another algorithm in a way that the new predominant color results to be RED too
After that the Hue shifting coloring is straighforward. We know that the predominant color is RED for all the images, and we'll shift the HUE values with a difference between the HSV value of the desired color and the HSV of the predominant color (RED).
Game over. We have a pretty universal way to color different images with hue shifting in a natural way.
Another question could be how to authomatically pre-shift the input images which predominant color is not black or white.
But this is another question.
Why this coloring method could be considered natural. Simply consider one thing. Generally the non dominant black or white colors are part of the shadows and light which gives a 3D feel to the images. On the other hand if my shoes are 100% black and i will tint them with some colors, they will no more be black. Color the dominant black cannot be achieved simply shifting the HSV parameters but other steps should be performed. The steps are the above described.