Deteksi Balon Ucapan Pada Komik Jepang Dengan Convolutional Neural Network, Canny Edge Detection dan Run Length Smooth Algorithm

Ricky Setiawan Saswono, Rudi Adipranata, Kartika Gunadi


Comic is an entertainment media that is usually used to fill free time. Comics themselves are already very well known in the world, especially comics from Japan. Comics from Japan, commonly called Manga, have a high level of popularity. The proof is a lot of Manga that is translated into each country's language. Examples such as One Piece that has been circulating in 43 countries. Even so the translation process is quite long especially in Japanese translation.

This research can be used to accelerate the translation process by using CNN and Canny Edge Detection to detect speech balloons in Manga. The detection results are segmented and with the help of OCR to digitize Japanese characters. Then use copy-paste techniques in an online dictionary or online translator to find the meaning of letters that are not understood. Because searching for letters from a physical dictionary (book) takes more time.

The results of the research to segment the speech balloon from Manga were successful but to classify the image in the form of a speech balloon or not with CNN was unsuccessful. Researchers assume because the dataset created is small in number or a problem during pre-processing.


CNN; Manga; RLSA; Canny Edge Detection; Speech bubble

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