Hiragana Handwriting Recognition Using Deep Neural Network Search

Rosalina rosalina, Johanes Parlindungan Hutagalung, Genta Sahuri


These days there is a huge demand in “storing the information available in paper documents into a computer storage disk”. Digitizing manual filled forms lead to handwriting recognition, a process of translating handwriting into machine editable text. The main objective of this research is to to create an Android application able to recognize and predict the output of handwritten characters by training a neural network model. This research will implement deep neural network in recognizing handwritten text recognition especially to recognize digits, Latin / Alphabet and Hiragana, capture an image or choose the image from gallery to scan the handwritten text from the image, use the live camera to detect the handwritten text real – time without capturing an image and could copy the results of the output from the off-line recognition and share it to other platforms such as notes, Email, and social media.


Hiragana; Handwriting Recognition; Deep Neural Network Search; Android; Real-time

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International Journal of Interactive Mobile Technologies (iJIM) – eISSN: 1865-7923
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