I want to detect an Eye, I have some code where I can detect blue color object, so if I made changes(how I can?) then it would be possible for me to detect an eye. As the below color has its own specific range value so, if I specify the eye color HSV value then can I detect EYE with this method.
In this below code I am going to detect BLUE Color Object, please tell me that where I do changes in my code so that I could get EYE using Open CV.
IplImage* GetThresholdedImage(IplImage* img)
{
// Convert the image into an HSV image
IplImage* imgHSV = cvCreateImage(cvGetSize(img), 8, 3);
cvCvtColor(img, imgHSV, CV_BGR2HSV);
IplImage* imgThreshed = cvCreateImage(cvGetSize(img), 8, 1);
//For detecting BLUE color i have this HSV value,
cvInRangeS(imgHSV, cvScalar(112, 100, 100), cvScalar(124, 255, 255), imgThreshed);//this will not recognize the yellow color
cvReleaseImage(&imgHSV);
return imgThreshed;
}
Eye detection is much easier with Haar classifier.
link here
Such a simple method may work at extracting a blue object using some thresholding but even if it could be adapted using a different colour black? blue? green? Everyone has different eye colours. I don't see a non hacky method working for you using blob extraction like this based on a HSV threshold value. This method works well on large blocks of the same colour, i.e. removing a blue background.
Look more at shape, everyone has different coloured eyes but the shape is circular/ellipse ish. There are varients of the Hough Transform for detecting circles.
...the Hough transform has been extended to identifying positions of
arbitrary shapes, most commonly circles or ellipses.
Related
Hellow there~
I'm working to make app.
This app need feature that detect Rubik's cube color(Realtime).
I'm using OpenCV to implement the feature.
I try to set up ROI and I detect color in ROI.
I know how to detect specific color.
I used inRange function on hsv channel image.
It's good working.
But now I don't know how to check color on specific region.
Forexample,
rubik's cube color array
(00)Red/(01)Blue/(02)Blue
(10)Green/(11)White/(12)Orange
(20)Yellow/(21)Blue/(22)White.
I want to know (0,0)'s color. It's red.
I use inRange function like this inRange((0,0)_image, lower_color, upper_color, color_mask).
Now how to check (0,0)_image's color what is?
How to know that is red?
Thank you for your attention.
Please let me know.
You should convert your image into HSV color space, where H stands for hue -- that's the color. Hue 0 is red, 0.3 is about green, 0.7 is like blue, you'll figure it out quite easily.
I would like to have a gradient which goes from black to transparent (not white). How can I achieve this?
From my attempt below I assume the gradient style color's alpha value is not considered:
gui_Footer.allStyles.apply {
backgroundType = Style.BACKGROUND_GRADIENT_LINEAR_VERTICAL
border = RoundRectBorder.create().topOnlyMode(true).cornerRadius(1f)
backgroundGradientEndColor = ColorUtil.BLACK
backgroundGradientStartColor = ColorUtil.argb(0, 255, 255, 255)
}
Gradients in Codename One ignore the alpha byte. While we could technically add support for alpha gradients it's not something that's planned at this time. You can probably generate such an image by manipulating the RGB data but it would be more efficient to just generate an RGB image of a gradient and draw it scaled.
Notice that this is generally the most efficient approach since the GPU works by drawing textures very efficiently. If an image is a power of 2 (e.g. 256x128 pixels) it can fit perfectly in a texture and it's drawn very fast. Much faster than our builtin gradients.
I am using FreeType to render some texts.
The surface where I want to draw the text is a bitmap image with format ARGB, pre-multiplied alpha.
The needed color of the text is also ARGB.
The rendered FT_Bitmap has format FT_PIXEL_MODE_LCD - it is as the text is rendered with white color on black background, with sub-pixel antialiasing.
So, for every pixel I have 3 numbers:
Da, Dr, Dg, Db - destination pixel ARGB (the background image).
Fr, Fg, Fb - FreeType rendered pixel (FT_Bitmap rendered with FT_RENDER_MODE_LCD)
Ca, Cr, Cg, Cb - The color of the text I want to use.
So, the question: How to properly combine these 3 numbers in order to get the result bitmap pixel.
The theoretical answers are OK and even better than code samples.
Interpet the FreeType data not as actual RGB colors (these 'raw' values are to draw text in black) but as intensities of the destination text color.
So the full intensity of each F color component is F*C/255. However, since your C also includes an alpha component, the intensity is scaled by it:
s' = F*C*A/(255 * 255)
assuming, of course, that F, C, and A are inside the usual range of 0..255. A is a fraction A/255, and the second division is to bring F*C back into the target range. s' is now the derived source color.
On to plotting it. Per color component, the new color gets add to D, and D in turn gets dimished by the source's alpha 255-A (scaled).
That leads to the full sum
D' = D*(255-A)/255 + F*C*A/(255 * 255)
equal to (moving one value to the right)
D' = (D*(255-A) + F*C*A/255)/255
for each separate channel r,g,b of D, F, C and A. The last one, alpha, also needs a separate calculation for each channel because your FreeType output data returns this format.
If the calculation is too slow, you could compare the visual result with not-LCD-optimized grayscale output from FreeType. I suspect that especially on 'busy' (not entirely monochrome) backgrounds the extra calculations are simply not worth it.
The numerical advantage of a pure grayscale input is that you only have to calculate A and 1-A once for each triplet of RGB colors.
The "background" also has an alpha channel but to draw text "on" it you can regard this as 'unused'. Drawing a transparent item onto another transparent item does not, in general, change its intrinsic transparency.
After some discovery, I found the right answer. It is disappointing.
It is impossible to draw subpixel rendered graphics (including fonts) on a transparent image with RGBA format.
In order to properly render such graphics, a format that supports separate alpha channels for every color is mandatory.
For example 48 bit per pixes: RrGgBg where r, g and b are the alpha channels for the red, green and blue collor channels respectively.
I am trying to find the Contours using
cvFindContours( gray, storage, &contour, sizeof(CvContour), CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE, cvPoint(0, 0));
and Canny but i am not able to dectect it.
Is there any way i can detect it.( all the processing is done in c)
First equalize image for better contrast. It will increase noise and other textures also but object will be quite visible.
Now, find gradient, it will evade most of gradual color and noise and some texture.
Now you can experiment with some thresholding, it will give good edge and region around shadow and object both.
To remove noise and texture, whole image can be median blurred with large kernel and then thresholded to get interesting region mask.
You can try multiple iteration of above method also. It lots of accuracy is not required, try blurring out texture.
I have a basic png file with two colors in it, green and magenta. What I'm looking to do is to take all the magenta pixels and make them transparent so that I can merge the image into another image.
An example would be if I have an image file of a 2D character on a magenta background. I would remove all the magenta in the background so that it's transparent. From there I would just take the image of the character and add it as a layer in another image so it looks like the character has been placed in an environment.
Thanks in advance.
That's the code i would use,
First, load your image :
IplImage *myImage;
myImage = cvLoadImage("/path/of/your/image.jpg");
Then use a mask like this to select the color, you should refer to the documentation. In the following, I want to select a blue (don't forget that in OpenCV images are in BGR format, therefore 125,0,0 is a blue (it corresponds to the lower bound) and 255,127,127 is blue with a certain tolerance and is the upper bound.
I chose lower and upper bound with a tolerance to take all the blue of your image, but you can select whatever you want...
cvInRangeS(image,
cvScalar(125.0, 0.0, 0.0),
cvScalar(255.0, 127.0, 127.0),
mask
);
Now we have selected the mask, let's inverse it (as we don't want to keep the mask, but to remove it)
cvNot(mask, mask);
And then copy your image with the mask,
IplImage *myImageWithTransparency; //You may need to initialize it before
cvCopy(myImage,myImageWithTransparency,mask);
Hope it could help,
Please refer to the OpenCVDocumentation for further information
Here it is
Julien,