Lampung handwritten character recognition
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Date
2016
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Abstract
Lampung script is a local script from Lampung province Indonesia. The script is a
non-cursive script which is written from left to right. It consists of 20 characters. It
also has 7 unique diacritics that can be put on top, bottom, or right of the character.
Considering this position, the number of diacritics augments into 12 diacritics. This
research is devoted to recognize Lampung characters along with diacritics. The
research aim to attract more concern on this script especially from Indonesian
researchers. Beside, it is also an endeavor to preserve the script from extinction.
The work of recognition is administered by multi steps processing system the so
called Lampung handwritten character recognition framework. It is started by a
preprocessing of a document image as an input. In the preprocessing stage, the input
should be distinguished between characters and diacritics. The character is classified
by a multistage scheme. The first stage is to classify 18 character classes and the
second stage is to classify special characters which consist of two components. The
number of classes after the second stage classification becomes 20 class. The diacritic
is classified into 7 classes. These diacritics should be associated to the characters to
form compound characters. The association is performed in two steps. Firstly, the
diacritic detects some characters nearby. The character with closest distance to that
diacritic is selected as the association. This is completed until all diacritics get their
characters. Since every diacritic already has one-to-one association to a character, the
pivot element is switched to a character in the second step. Each character collects
all its diacritics as a composition of the compound characters. This framework has
been evaluated on Lampung dataset created and annotated during this work and
is hosted at the Department of Computer Science, TU Dortmund, Germany. The
proposed framework achieved 80.64% recognition rate on this data.
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Keywords
Lampung script, Handwritten character recognition, Diacritic recognition, Lampung Skript, Handgeschriebene Zeichenerkennung, Diakritische Zeichenerkennung