How to find the two most dominant colors in an image?

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Another approach:

1. Optional: Quantize all colors of your image into e.g. 16 different colors per channel
2. Use k-means with k=2 and cluster all colors (one 3-d color vector per pixel) based on the euclidean distance between the colors. A small number of iterations should be sufficient. The two resulting clusters then separate the colors within your image into two classes.
3. Use the two cluster centroids (=color means) as your dominant colors.

Converting RGB to HSV colour space may help you for colour based segmentation. You can refer this link for more information http://www.shervinemami.info/colorConversion.html ,where you can download ColorWheelHSV and which may help you to get an visual idea about HSV and RGB colour range.

Perform an RGB histogram calculation of your image. Look inside the R, G and B channel which two components are the largest (background and color of letters). Then combine these largest values to detect the actual color that is dominant by combining the three channels into a single color.

If it is segmentation that you want to achieve, you could also perform a RGB to grayscale conversion and then perform the histogram voting to know the two dominant grayscale values.

Not sure which functions compute the histograms of an input image, but do a search on histogram in the openCV documentation: http://docs.opencv.org/

Cheers!

There is an awesome python tutorial added here with visualization using color quantization.

If you are are looking for method to isolate forground text from back ground , i read that the best method till now is SWT (Stroke Width Transform ) , the method is announced on 2010 by Epshtein and others in 2010 you can find the implementation and some description in the following link SWT implementation

the method works for any color text on any background , also it works when there is alot of text written in diffirent colors , you can use it as generlized text detection method