  Handwritten numerals of different languages have various characteristics.
Similarities and dissimilarities of the languages can be measured by analyzing
the extracted features of the numerals. Handwritten numeral datasets are
available and accessible for many renowned languages of different regions. In
this paper, several handwritten numeral datasets of different languages are
collected. Then they are used to find the similarity among those written
languages through determining and comparing the similitude of each handwritten
numerals. This will help to find which languages have the same or adjacent
parent language. Firstly, a similarity measure of two numeral images is
constructed with a Siamese network. Secondly, the similarity of the numeral
datasets is determined with the help of the Siamese network and a new random
sample with replacement similarity averaging technique. Finally, an
agglomerative clustering is done based on the similarities of each dataset.
This clustering technique shows some very interesting properties of the
datasets. The property focused in this paper is the regional resemblance of the
datasets. By analyzing the clusters, it becomes easy to identify which
languages are originated from similar regions.
