Rosetta: Large scale system for text detection and recognition in images
Abstract
In this paper we present a deployed, scalable optical character recognition (OCR) system, which we call Rosetta, designed to process images uploaded daily at Facebook scale. Sharing of image content has become one of the primary ways to communicate information among internet users within social networks such as Facebook and Instagram, and the understanding of such media, including its textual information, is of paramount importance to facilitate search and recommendation applications. We present modeling techniques for efficient detection and recognition of text in images and describe Rosetta's system architecture. We perform extensive evaluation of presented technologies, explain useful practical approaches to build an OCR system at scale, and provide insightful intuitions as to why and how certain components work based on the lessons learnt during the development and deployment of the system.
Cite
@article{arxiv.1910.05085,
title = {Rosetta: Large scale system for text detection and recognition in images},
author = {Fedor Borisyuk and Albert Gordo and Viswanath Sivakumar},
journal= {arXiv preprint arXiv:1910.05085},
year = {2019}
}
Comments
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD) 2018, London, United Kingdom