Histogram concavity analysis as an aid in threshold selection

A well-known heuristic for segmenting an image into gray level subpopulations is to select thresholds at the bottoms of valleys on the image´s histogram. When the subpopulations overlap, valleys may not exist, but it is often still possible to define good thresholds at the `shoulders´ of histogram peaks. Both valleys and shoulders correspond to concavities on the histogram, and this suggests that it should be possible to find good candidate thresholds by analyzing the histogram´s concavity structure. Histogram concavity analysis as an approach to threshold selection is investigated and its performance on a set of histograms of infrared images of tanks is illustrated.