Best practice, to detect if a Mat is black and White in Opencv

Question

I would like to know if the image I read is a Black and white or colored image. I use Opencv for all my process. In order to detect it, I currently read my image, convert it from BGR2GRAY and I compare Histogram of the original(read as BGR) to the histogram of the second (known as B&W).

In pseudo code this looks like that:

cv::Mat img = read("img.png", -1);
cv::Mat bw = cvtColor(img.clone(), bw, CV_BGR2GRAY);

if (computeHistogram(img) == computeHistogram(bw))
     cout << "Black And White !"<< endl;

Is there a better way to do it ? I am searching for the lightest algo I can Implement and best practices.

Thanks for the help.

Edit: I forgot to say that I convert my images in HSL in order to compare Luminance Histograms.

When you say "black & white", do you mean greyscale, or a binary image? — Aurelius, Jul 03 '13 at 14:46
What is the relevance of converting to HSL? Are you trying to do the comparison in HSL color space? Or is your `bw` image actually in greyscale? — Aurelius, Jul 03 '13 at 14:53
No you can have some black and white images with 3 channels... — Poko, Jul 03 '13 at 15:32

score 2 · Answer 1 · answered Jul 03 '13 at 16:31

2

Storing grayscale images in RGB format causes all three fields to be equal. It means for every pixel in a grayscale image saved in RGB format we have R = G = B. So you can easily check this for your image.

answered Jul 03 '13 at 16:31

Kourosh

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Best practice, to detect if a Mat is black and White in Opencv

1 Answers1