Rosetta: Large Scale System for Text Detection and Recognition in Images

被引:197
|
作者
Borisyuk, Fedor [1 ]
Gordo, Albert [1 ]
Sivakumar, Viswanath [1 ]
机构
[1] Facebook Inc, Menlo Pk, CA 94025 USA
关键词
Optical character recognition; text detection; text recognition;
D O I
10.1145/3219819.3219861
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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 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.
引用
收藏
页码:71 / 79
页数:9
相关论文
共 50 条
  • [31] Text Detection and Recognition from Scene Images using MSER and CNN
    Choudhary, Savita
    Singh, Nikhil Kumar
    Chichadwani, Sanjay
    2018 SECOND INTERNATIONAL CONFERENCE ON ADVANCES IN ELECTRONICS, COMPUTERS AND COMMUNICATIONS (ICAECC), 2018,
  • [32] AIFood: A Large Scale Food Images Dataset for Ingredient Recognition
    Lee, Gwo Giun
    Huang, Chin-Wei
    Chen, Jia-Hong
    Chen, Shih-Yu
    Chen, Hsiu-Ling
    PROCEEDINGS OF THE 2019 IEEE REGION 10 CONFERENCE (TENCON 2019): TECHNOLOGY, KNOWLEDGE, AND SOCIETY, 2019, : 802 - 805
  • [33] Text Detection and Recognition for X-ray Weld Seam Images
    Zheng, Qihang
    Zhang, Yaping
    APPLIED SCIENCES-BASEL, 2024, 14 (06):
  • [34] SURFACE-TO-AIR MISSILE SITES DETECTION AND RECOGNITION WITH LARGE-SCALE REMOTE SENSING IMAGES
    Zhao, Tianming
    Gao, Peng
    Tao, Zeyuan
    Tian, Tian
    Tian, Jinwen
    2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022), 2022, : 3103 - 3106
  • [35] Text detection and recognition based on a lensless imaging system
    Zhang, Yinger
    Wu, Zhouyi
    Lin, Peiying
    Wu, Yuting
    Wei, Lusong
    Huang, Zhengjie
    Huangfu, Jiangtao
    APPLIED OPTICS, 2022, 61 (14) : 4177 - 4186
  • [36] Detection of Nude Images on Large Scale Using Hadoop
    Ahuja, Chirag
    Baghel, Anurag Singh
    Singh, Gotam
    2015 2ND INTERNATIONAL CONFERENCE ON COMPUTING FOR SUSTAINABLE GLOBAL DEVELOPMENT (INDIACOM), 2015, : 849 - 853
  • [37] Large-Lexicon Attribute-Consistent Text Recognition in Natural Images
    Novikova, Tatiana
    Barinova, Olga
    Kohli, Pushmeet
    Lempitsky, Victor
    COMPUTER VISION - ECCV 2012, PT VI, 2012, 7577 : 752 - 765
  • [38] TOWARDS LARGE-SCALE BUILDING ATTRIBUTE MAPPING USING CROWDSOURCED IMAGES: SCENE TEXT RECOGNITION ON FLICKR AND PROBLEMS TO BE SOLVED
    Sun, Y.
    Kruspe, A.
    Meng, L.
    Tian, Y.
    Hoffmann, E. J.
    Auer, S.
    Zhu, X. X.
    GEOSPATIAL WEEK 2023, VOL. 48-1, 2023, : 225 - 232
  • [39] Automatic Detection and Recognition of Text-Based Traffic Signs from Images
    Oliveira, G.
    Silva, F.
    Pereira, D.
    Almeida, L.
    Artero, A.
    Bonora, A.
    de Albuquerque, V.
    IEEE LATIN AMERICA TRANSACTIONS, 2018, 16 (12) : 2947 - 2953
  • [40] Detection and Recognition of Text Embedded in Online Images via Neural Context Models
    Kang, Chulmoo
    Kim, Gunhee
    Yoo, Suk I.
    THIRTY-FIRST AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2017, : 4103 - 4110