Technique to introduce normalisation/consistency to std dev comparison? - opencv

Question

I am implementing a very simple segmentation algorithm for single channel images. The algorithm works like so:
For a single channel image:
Calculate the standard deviation, ie, measure how much the luminosity varies across the image.
If the stddev > 15 (aka threshold):
Divide the image into 4 cells/images
For each cell:
Repeat step 1 and step 2 (go recursive)
Else:
Draw a rectangle on the source image to signify a segment lies in these bounds.
My problem occurs because my threshold is constant and when I go recursive 15 is not longer a good signifier of whether that image is homogeneous or not. How can I introduce consistency/normalisation to my homogeneity check?
Should I resize each image to the same size (100x100)? Should my threshold be formula? Say 15 / img.rows * img.cols or 15 / MAX_HISTOGRAM_PEAK?
Edit Code:
void split_mat(const Mat& src, Mat& split1, Mat& split2, Mat& split3, Mat& split4) {
split1 = Mat(src, Rect(Point(0, 0), Point(src.cols / 2, src.rows / 2)));
split1 = Mat(src, Rect(Point(src.cols/2, 0), Point(src.cols, src.rows / 2)));
split3 = Mat(src, Rect(Point(0, src.rows/2), Point(src.cols / 2, src.rows)));
split4 = Mat(src, Rect(Point(src.cols/2, src.rows/2), Point(src.cols, src.rows)));
}
void segment_by_homogeny(const Mat& src, double threshold) {
Scalar mean, stddev;
meanStdDev(src, mean, stddev);
double dev = stddev[0]; // / (src.rows * src.cols) * 100.0;
if (dev >= threshold) {
Mat s1, s2, s3, s4;
split_mat(src, s1, s2, s3, s4);
// Go recursive and segment each sub-segment where necessary
segment_by_homogeny(s1, threshold);
segment_by_homogeny(s2, threshold);
segment_by_homogeny(s3, threshold);
segment_by_homogeny(s4, threshold);
}
else {
// Store 'segment' in global vector 'images'
// and write std dev on it
char d[255];
sprintf_s(d, "Std Dev: %f", stddev[0]);
putText(src, d, cvPoint(30, 60),
FONT_HERSHEY_COMPLEX_SMALL, 0.7, cvScalar(200, 200, 250), 1, CV_AA);
images.push_back(src);
}
}
// current usage for the example image results in inifinite recursion.
// The green and red segment never has a std dev < 25
segment_by_homogeny(img, 25);
I am expecting my algorithm to produce the following 5 segments:

Answer 1

You can simplify your algorithm. Because you want to divide the given region into 4 subregions, you can first divide it into the 4 subregions, then calculate the average luminosity value for each, and have your threshold on the difference between these neighbor values.