“…The noise in the data resulted in binarisation failure and missing data in Figure 7-d, while the overlapping line created an occluded segment in Figure 7-c. On the other hand, although the handwritten segments shown in Figure 7-e to -h have close regularities with machine-printed text, they are correctly classified as handwritten since none of the gallery characters can produce a matching score higher than the threshold T . Because of the high similarity with the machine-printed sample, the geometric features, such as area and rectangularity used in [6], [7], [10], [12], fail to create separable classes and the samples will wrongly be classified as machine-printed. Table 1 shows the comparison of our approach with the results provided by Zagoris et al [3], [4], in which 15% of the samples in the PRImA-NHM dataset are utilised for train and the remaining 85% for the test phase.…”