Heuristic threshold for Histogram-based Binarization of Grayscale Images

The development of a Virtual Lab to perform experiments on histogram-based binarization of grey-leveled images is reported. With the aim of automatizing the binarization process, a Heuristic Binarization Threshold is introduced. Once the histogram of a grayscale input image is obtained, the module calculates a Heuristic Threshold by taking the weighted average of the foreground grey levels of the image. Next those pixels in input image whose grey levels are above this threshold are highlighted. Although still not experimentally optimum, this heuristic threshold provides a first approximation towards automatic binarization of greyscale images.