Analisis Perbandingan Optical Character Recognition Google Vision dengan Microsoft Computer Vision pada Pembacaan KTP-el

Abstract

In this era, the need of digital data is rapidly increasing. Electronic Residental Identity Card or KTP-el is the official identity card for resident of Indonesia. One fast way to extract information on an image is by using OCR/Optical Character Recognition. Competition between Google Vision API and Microsoft Computer Vision in providing OCR service encourage companies to choose the right provider. Method conducted in this research including literature review on both OCR service provider, identification and KTP-el sample image retrieval, data grouping, code implementation and accuracy testing, result analysis and discussion, and conclusion. The result of this research show that Microsoft Computer Vision have better accuracy in reading characters in KTP-el with an accuracy percentage of 0,81% to 15,8% difference to Google Vision. Google Vision has competitive accuracy, but suffers from deficiencies when reading KTP-el with blur and noise.