Natural Scene Text Detection Based on Multi-Channel FASText

被引:0
作者
Guo Chenfeng [1 ]
Liu Juhua [1 ]
机构
[1] Wuhan Univ, Sch Printing & Packaging, Wuhan, Hubei, Peoples R China
来源
PROCEEDINGS OF THE 2017 2ND INTERNATIONAL CONFERENCE ON AUTOMATIC CONTROL AND INFORMATION ENGINEERING (ICACIE 2017) | 2017年 / 119卷
基金
中国国家自然科学基金;
关键词
multi-channel; FASText; natural scene; text detection; LOCALIZATION;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In view of the complexity of background and the variety of text in natural scene images, a multi-channel FASText based text detection method for natural scene images is proposed. To detect more texts as much as possible, the character candidates are extracted by proposed multi-channel FASText algorithm from the R, G and B component image respectively. Then, texture features of the character candidates are extracted to train a random forest character classifier and the non-characters are eliminated. At last, the character regions are merged into text regions according to the color distance feature and geometric adjacency feature. The proposed approach on ICDAR 2013 dataset achieves 76.76%, 80.17%, and 78.43% in recall rate, precision rate and f-score respectively. Compared to other state-of-the-art methods, both the recall rate and f-score are improved. Experimental result shows that the proposed method is effective to natural scene text detection.
引用
收藏
页码:16 / 20
页数:5
相关论文
共 10 条
  • [1] Random forests
    Breiman, L
    [J]. MACHINE LEARNING, 2001, 45 (01) : 5 - 32
  • [2] FASText: Efficient Unconstrained Scene Text Detector
    Busta, Michal
    Neumann, Lukas
    Matas, Jiri
    [J]. 2015 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV), 2015, : 1206 - 1214
  • [3] Histograms of oriented gradients for human detection
    Dalal, N
    Triggs, B
    [J]. 2005 IEEE COMPUTER SOCIETY CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, VOL 1, PROCEEDINGS, 2005, : 886 - 893
  • [4] Text Localization in Natural Images using Stroke Feature Transform and Text Covariance Descriptors
    Huang, Weilin
    Lin, Zhe
    Yang, Jianchao
    Wang, Jue
    [J]. 2013 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV), 2013, : 1241 - 1248
  • [5] ICDAR 2013 Robust Reading Competition
    Karatzas, Dimosthenis
    Shafait, Faisal
    Uchida, Seiichi
    Iwamura, Masakazu
    Gomez i Bigorda, Lluis
    Robles Mestre, Sergi
    Mas, Joan
    Fernandez Mota, David
    Almazan Almazan, Jon
    Pere de las Heras, Lluis
    [J]. 2013 12TH INTERNATIONAL CONFERENCE ON DOCUMENT ANALYSIS AND RECOGNITION (ICDAR), 2013, : 1484 - 1493
  • [6] Robust text detection via multi-degree of sharpening and blurring
    Liu, Juhua
    Su, Hai
    Yi, Yaohua
    Hu, Wenbin
    [J]. SIGNAL PROCESSING, 2016, 124 : 259 - 265
  • [7] Real-Time Lexicon-Free Scene Text Localization and Recognition
    Neumann, Lukas
    Matas, Jiri
    [J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2016, 38 (09) : 1872 - 1885
  • [8] Multiresolution gray-scale and rotation invariant texture classification with local binary patterns
    Ojala, T
    Pietikäinen, M
    Mäenpää, T
    [J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2002, 24 (07) : 971 - 987
  • [9] Detecting Text in Natural Image with Connectionist Text Proposal Network
    Tian, Zhi
    Huang, Weilin
    He, Tong
    He, Pan
    Qiao, Yu
    [J]. COMPUTER VISION - ECCV 2016, PT VIII, 2016, 9912 : 56 - 72
  • [10] Robust Text Detection in Natural Scene Images
    Yin, Xu-Cheng
    Yin, Xuwang
    Huang, Kaizhu
    Hao, Hong-Wei
    [J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2014, 36 (05) : 970 - 983