KLASIFIKASI CITRA TEKS UNTUK PENERJEMAHAN BAHASA DAERAH MENGGUNAKAN ARTIFICIAL NEURAL NETWORK
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Institusion
Universitas Pembangunan Nasional Veteran Jakarta
Author
Farel Fathurrahman, .
Subject
QA75 Electronic computers. Computer science
Datestamp
2022-01-12 05:29:34
Abstract :
Local language are used to communicate with each other in certain areas. Many factors make the young generation's awareness to preserve the local language. One of them is still lack of means to access the local languages, so this is one of the problems that occurs. In this study, would design a translation system of an image containing Indonesian text into a local language text. This research starts from the pre-process stage, character segmentation techniques in the image using Connected Component Analysis labeling. After that, the image is extracted then the character image is classifying using the Artificial Neural Network method. The next step is to merge characters into a text. After that, the translation process uses the Levensthein algorithm to match the results of the text classification with local language. This research is expected to be able to translate the image of Indonesian texts into local language text, to help preserve local language in Indonesia.
Local language are used to communicate with each other in certain areas. Many factors make the young generation's awareness to preserve the local language. One of them is still lack of means to access the local languages, so this is one of the problems that occurs. In this study, would design a translation system of an image containing Indonesian text into a local language text. This research starts from the pre-process stage, character segmentation techniques in the image using Connected Component Analysis labeling. After that, the image is extracted then the character image is classifying using the Artificial Neural Network method. The next step is to merge characters into a text. After that, the translation process uses the Levensthein algorithm to match the results of the text classification with local language. This research is expected to be able to translate the image of Indonesian texts into local language text, to help preserve local language in Indonesia.
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