In general, the morphological filtering process can remove
signal noise or small grains such as seeds from X-ray images
of fruit. As shown in Fig. 10a, the X-ray image of a guava contains
several infestation sites, and the result of segmentation
after adaptive thresholding without morphological filtering is
shown in Fig. 10b. By removing small spots using morphological
filtering with three iterations, small spots of noise and
granular seeds were successfully removed leaving the segmented
infestation site as shown in Fig. 10c. However, in
another case of peach as shown in Fig. 10d, the soft tissue
around the pit has similar grey level and size as the infestation
site on the top of the fruit. The morphological filtering
segmented both spots but was not successful in differentiating
the infestation site and the normal tissue (Fig. 10f). In most
cases, adjusting the iteration number of the morphological filtering can successfully segregate infestation site from the
noise or granular texture in the X-ray image of fruits. When
the size and grey level of the segmented spots are similar, the
current segmentation algorithm has its limitations and thus
other geometric features of segmented spots such as shape or
length needs to be considered, if necessary.