The postprocessing step used in Yanowitz and Bruckstein's binarization method removes "ghost" objects, and can be incorporated into other methods as well. The average gradient value at the edge of each printed object is calculated. Objects having an average gradient below a threshold TP are labeled as misclassified, and are removed. The main steps of the algorithm are given below:
1. Smooth the original image by a (3x3) mean filter to remove noise.
2. Calculate the gradient magnitude image G of the smoothed image, using, e.g., Sobel's edge operator.
3. Select a value for TP.
4. For all 4-connected print components, calculate the average gradient of the edge pixels. Edge pixels are print pixels that are 4-connected to the background. Remove print components having an average edge gradient below the threshold TP.
Øivind Due Trier , Torfinn Taxt. Evaluation of Binarization Methods for Document Images (1995). Available at: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.53.4360
Jan Motl (2020). Remove ghosts from binarized images (https://www.mathworks.com/matlabcentral/fileexchange/41786-remove-ghosts-from-binarized-images), MATLAB Central File Exchange. Retrieved .
Added example image.