![]() ![]() ![]() In practice, instead of minimizing vw(t), the algorithm maximizes the "between-class" variance. This variance is sometimes called the "within-class" variance, and can be expressed as: It picks the gray level (threshold) that minimizes the sum of the two normalized variances. The trick is to find where the two distributions intersect (By the way, even when the histogram has a clear valley, the threshold is not necessarily at the bottom of that valley).įor each gray level (t) along the histogram (h(t)), the algorithm calculates the variance of the two portions of the histogram lying on each side of t (v1(t) and v2(t)). ![]() The threshold is usually not obvious because the two distributions overlap. It assumes that the gray level histogram is the sum of two normal intensity distributions (two classes): Object pixels and background pixels. Auto-threshold (Count/Size) is an iterative method. ![]()
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