Alat Koreksi dan Rekontruksi Tulisan pada Dokumen Lama Bahasa Indonesia Berbasis Mini PC - Rifki Suwandi; Werman Kasoep; Ramon Luthvi Destria (Universitas Andalas, 2023)
In the digital era, preserving old documents to prevent damage is a significant challenge. One solution to this problem is to reconstruct damaged or lost documents using image processing and natural language processing technologies. This article discusses the design of a tool for correcting and reconstructing writing in old papers and documents that can be implemented on a mini PC. The tool uses state-of-the-art algorithms such as Convolutional Neural Network (CNN) for character recognition and Optical Character Recognition (OCR), as well as Image Inpainting and Sequence-to-Sequence (Seq2Seq) algorithms for document reconstruction. Test results show that this tool can recognize characters with high accuracy and reconstruct damaged or lost documents effectively.