Abstract:
In Sri Lanka post offices play the most significant role when considering sharing the
letters, bills, bank statements, sending parcels, and many more. According to the
performance report of the postal department in 2018, 258,866 letters had been sorted
and delivered through the Central Mail Exchange per day in Sri Lanka [1]. This
mailing process could be made more effective and systematic by reducing the time
of the manual process and the human error rate. There are many existing systems
regarding automating the mail sorting process in other countries. As an example,
Amazon deploys a robot allowing it to receive a package and deposit it in the correct
location in the center according to the zip code by reducing miss-sorts [2]. However,
in Sri Lanka, there is no proper system to automate the mail sorting process because,
in the context of the Sinhala language, the alphabet consists of symbols that are
complex and vary in shape and dimensions. Identifying each letter or modifier in a
Sinhala text image is a challenge due to features such as overlapping or touching
characters, cursive or non-cursive characters, and vary in shape or dimension of the
characters from person to person, etc.
This research proposes a solution to implement an automated system that can take
an envelope image and classify that envelope into relevant postal division using
postal code. The proposed methodology has two main phases known as identifying
the relevant postal division and digitization of the mail process. The first phase
consists of three sub-processes: preprocessing and identifying elements, segmenting
and character recognition, error correction, and identifying relevant postal code. In
the second phase, the proposed system keeps a record of mail details that are passed
by the system.
