Perancangan dan Pembuatan Alat untuk Mendeteksi Teks Hangul dan Inggris pada Menu Makanan Menggunakan metode OCR (Optical Character Recognition) - Nimatul Mamuriyah; Jacky Jacky (Telcomatics, 2021)
Korean language has a different form of characters from the letters of the alphabet so that not everyone can read Korean characters. The number of Muslims in Korea who are in the minority results in the Korean people's understanding of halal food being very minimal. As a result, foreign tourists, especially Muslim tourists who come to Korea have difficulty choosing halal food. Based on these problems, the topic of this research is based on the image processing system (Image Processing) that is designed is the detection of the letters of the alphabet and Hangul (Korean characters) using the OCR (Optical Character Recognition) and Raspberry Pi as data processing so that it can recognize letter characters Hangul and alphabet that are already available in the database. The workings of this system are first to create a database of food data and certain words related to food menus. Then by using the Pi camera, scanning of the food menu is done. The data obtained will be processed by Raspberry Pi so that the system is able to detect food menus correctly. The results show that the system is able to detect food menus from text localization with an average accuracy rate of 88,333%. By using 4 different font types, the English text shows OCR data train still needs to be improved.