Abstract:
The esports industry in Thailand has gained widespread attention, with several organizations starting to organize RoV tournaments to enhance the excitement of the competitions. Consequently, statistics of each match arecollected and utilized as data for promoting each round of the competition. Conventionally, the method of data collection involves capturing images of the match results and manually inputting the information for further analysis. However, this process often leads to errors or delays, particularly when dealing with a large volume of data. To address these issues, the researchers explore the use of Optical Character Recognition (OCR) for data extraction from images, aiming to reduce errors associated with manual data entry and improve the convenience and efficiency of data collection. A comparative analysis of image data extraction performance between pytesseract and easyOCR reveals that pytesseract provides superior data extraction results and requires lesstime for the extraction process.
