Object Detection and Text Recognition in Large-scale Technical Drawings

被引:7
|
作者
Nguyen, Trang M. [1 ,2 ]
Long Van Pham [1 ]
Chien Chu Nguyen [1 ]
Vinh Van Nguyen [1 ,2 ]
机构
[1] VNUH, Univ Engn & Technol, Hanoi, Vietnam
[2] FPT Software, QAI, Hanoi, Vietnam
关键词
Digital Transformation; Object Detection; Optical Character Recognition;
D O I
10.5220/0010314406120619
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 digital transformation era, the demand for automatic pattern extraction from printed materials has never been higher, making it one of the most eminent problems nowadays. In this paper, we propose a new method for pattern recognition in highly complex technical drawings. Our method is a pipeline system that includes two phases: (1) detecting the objects that contain the patterns of interest with improvements to processing large-scale image, and (2) performing character recognition on the objects if they are text patterns with improvements to post-processing task. Our experiments on nearly five thousand real technical drawings show promising results and the capability to reduce manual labeling effort to a great extent.
引用
收藏
页码:612 / 619
页数:8
相关论文
共 50 条
  • [1] Implementation of Large-scale Object Recognition System
    Kim, Min-Uk
    Yoon, Kyoungro
    2013 INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE AND APPLICATIONS (ICISA 2013), 2013,
  • [2] Fuzzy relational distance for large-scale object recognition
    Huet, B
    Hancock, ER
    1998 IEEE COMPUTER SOCIETY CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, PROCEEDINGS, 1998, : 138 - 143
  • [3] Relative Attributes For Large-scale Abandoned Object Detection
    Fan, Quanfu
    Gabbur, Prasad
    Pankanti, Sharath
    2013 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV), 2013, : 2736 - 2743
  • [4] Image Models for large-scale Object Detection and Classification
    Kralev, Jordan
    Koeva, Svetla
    PROCEEDINGS OF THE FIFTH INTERNATIONAL CONFERENCE COMPUTATIONAL LINGUISTICS IN BULGARIA, CLIB 2022, 2022, : 190 - 201
  • [5] Salient object detection on large-scale video data
    Zhang, Shile
    Fan, Jianping
    Lu, Hong
    Xue, Xiangyang
    2007 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, VOLS 1-8, 2007, : 3704 - +
  • [6] A Large-Scale 3D Object Recognition dataset
    Solund, Thomas
    Buch, Anders Glent
    Kruger, Norbert
    Aanaes, Henrik
    PROCEEDINGS OF 2016 FOURTH INTERNATIONAL CONFERENCE ON 3D VISION (3DV), 2016, : 73 - 82
  • [7] Rosetta: Large Scale System for Text Detection and Recognition in Images
    Borisyuk, Fedor
    Gordo, Albert
    Sivakumar, Viswanath
    KDD'18: PROCEEDINGS OF THE 24TH ACM SIGKDD INTERNATIONAL CONFERENCE ON KNOWLEDGE DISCOVERY & DATA MINING, 2018, : 71 - 79
  • [8] Collaborative Camouflaged Object Detection: A Large-Scale Dataset and Benchmark
    Zhang, Cong
    Bi, Hongbo
    Xiang, Tian-Zhu
    Wu, Ranwan
    Tong, Jinghui
    Wang, Xiufang
    IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2023, 35 (12) : 1 - 15
  • [9] Efficient Maximum Appearance Search for Large-Scale Object Detection
    Chen, Qiang
    Song, Zheng
    Feris, Rogerio
    Datta, Ankur
    Cao, Liangliang
    Huang, Zhongyang
    Yan, Shuicheng
    2013 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2013, : 3190 - 3197
  • [10] Efficient Point Process Inference for Large-scale Object Detection
    Pham, Trung T.
    Rezatofighi, Seyed Hamid
    Reid, Ian
    Chin, Tat-Jun
    2016 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2016, : 2837 - 2845