Abstract

Katakana is one of the traditional Japanese letters used to absorption words from other languanges. In the inttroduction of an object a learning process is needed, which is obtained through the characteristics and experience of observing similar objects after being acquired. But manually it is quite difficult to distinguish between 5 hiragana vowels starting from the image data acquisition process, image processing, feature extraction using Gray Level Co-occurance Matrix (GLCM) while classifiers use the euclidean distance method. The results of the tests carried out showed an accuracy rate of around 78% using the euclidean method.

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