Scene Text Detection with Inception Text Proposal Generation Module

被引:1
|
作者
Zhang, Hang [1 ,2 ]
Liu, Jiahang [1 ]
Chen, Tieqiao [1 ,2 ]
机构
[1] Chinese Acad Sci, Xian Inst Opt & Precis Mech, Xian 710119, Shaanxi, Peoples R China
[2] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
来源
ICMLC 2019: 2019 11TH INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND COMPUTING | 2019年
关键词
Text detection; convolutional neural network; region proposal network; natural images;
D O I
10.1145/3318299.3318373
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Most scene text detection methods based on deep learning are difficult to locate texts with multi-scale shapes. The challenges of scale robust text detection lie in two aspects: 1) scene text can be diverse and usually exists in various colors, fonts, orientations, languages, and scales in natural images. 2) Most existing detectors are difficult to locate text with large scale change. We propose a new Inception-Text module and adaptive scale scaling test mechanism for multi-oriented scene text detection. the proposed algorithm enhances performance significantly, while adding little computation. The proposed method can flexibly detect text in various scales, including horizontal, oriented and curved text. The proposed algorithm is evaluated on three recent standard public benchmarks, and show that our proposed method achieves the state-of-the-art performance on several benchmarks. Specifically, it achieves an F-measure of 93.3% on ICDAR2013, 90.47% on ICDAR2015 and 76.08%(1) on ICDAR2017 MLT.
引用
收藏
页码:456 / 460
页数:5
相关论文
共 50 条
  • [31] Label Enhancement for Scene Text Detection
    MEI Junjun
    GUAN Tao
    TONG Junwen
    ZTE Communications, 2022, 20 (04) : 89 - 95
  • [32] Scene text detection and recognition: a survey
    Fatemeh Naiemi
    Vahid Ghods
    Hassan Khalesi
    Multimedia Tools and Applications, 2022, 81 : 20255 - 20290
  • [33] Review of Scene Text Detection and Recognition
    Lin, Han
    Yang, Peng
    Zhang, Fanlong
    ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING, 2020, 27 (02) : 433 - 454
  • [34] Scene Text Detection with Selected Anchors
    Zhu, Anna
    Du, Hang
    Xiong, Shengwu
    2020 25TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR), 2021, : 6608 - 6615
  • [35] AdaBoost for Text Detection in Natural Scene
    Lee, Jung-Jin
    Lee, Pyoung-Hean
    Lee, Seong-Whan
    Yuille, Alan
    Koch, Christof
    11TH INTERNATIONAL CONFERENCE ON DOCUMENT ANALYSIS AND RECOGNITION (ICDAR 2011), 2011, : 429 - 434
  • [36] Feature Fusion for Scene Text Detection
    Zhu, Zhen
    Liao, Minghui
    Shi, Baoguang
    Bai, Xiang
    2018 13TH IAPR INTERNATIONAL WORKSHOP ON DOCUMENT ANALYSIS SYSTEMS (DAS), 2018, : 193 - 198
  • [37] Could scene context be beneficial for scene text detection?
    Zhu, Anna
    Gao, Renwu
    Uchida, Seiichi
    PATTERN RECOGNITION, 2016, 58 : 204 - 215
  • [38] REFINETEXT: REFINING MULTI-ORIENTED SCENE TEXT DETECTION WITH A FEATURE REFINEMENT MODULE
    Xie, Pengyuan
    Xiao, Jing
    Cao, Yang
    Zhu, Jia
    Khan, Asad
    2019 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO (ICME), 2019, : 1756 - 1761
  • [39] Arbitrarily Shaped Scene Text Detection With a Mask Tightness Text Detector
    Liu, Yuliang
    Jin, Lianwen
    Fang, Chuanming
    IEEE TRANSACTIONS ON IMAGE PROCESSING, 2020, 29 : 2918 - 2930
  • [40] Text Flow: A Unified Text Detection System in Natural Scene Images
    Tian, Shangxuan
    Pan, Yifeng
    Huang, Chang
    Lu, Shijian
    Yu, Kai
    Tan, Chew Lim
    2015 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV), 2015, : 4651 - 4659