{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T12:21:23Z","timestamp":1784031683382,"version":"3.55.0"},"reference-count":63,"publisher":"Public Library of Science (PLoS)","issue":"4","license":[{"start":{"date-parts":[[2024,4,16]],"date-time":"2024-04-16T00:00:00Z","timestamp":1713225600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100013071","name":"Major Program of National Fund of Philosophy and Social Science of China","doi-asserted-by":"publisher","award":["20BGL141"],"award-info":[{"award-number":["20BGL141"]}],"id":[{"id":"10.13039\/501100013071","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"<jats:p>It is challenging to detect arbitrary-shape text accurately and effectively in natural scenes. While many methods have been implemented for arbitrary-shape text detection, most cannot achieve real-time detection or meet practical needs. In this work, we propose a YOLOv6-based detector that can effectively implement arbitrary-shape text detection and achieve real-time detection. We include two additional branches in the neck part of the YOLOv6 network to adapt the network to text detection, and the output side uses the pixel aggregation (PA) algorithm to decouple the PA output to use it as the detection head of the model. Experiments on benchmark Total-Text, CTW1500, ICDAR2015, and MSRA-TD500 showed that the proposed method outperformed competing methods in terms of detection accuracy and running time. Specifically, our method achieved an F-measure of 84.1% at 291.8 FPS for 640 \u00d7 640 Total-Text images and an F-measure of 81.5% at 199.6 FPS for 896 \u00d7 896 ICDAR2015 incidental text images.<\/jats:p>","DOI":"10.1371\/journal.pone.0302234","type":"journal-article","created":{"date-parts":[[2024,4,16]],"date-time":"2024-04-16T17:33:36Z","timestamp":1713288816000},"page":"e0302234","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":4,"title":["A real-time arbitrary-shape text detector"],"prefix":"10.1371","volume":"19","author":[{"given":"Manhuai","family":"Lu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Langlang","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4958-2043","authenticated-orcid":true,"given":"Chin-Ling","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2024,4,16]]},"reference":[{"key":"pone.0302234.ref001","unstructured":"Kang C, Kim G, Yoo SI. Detection and recognition of text embedded in online images via neural context models. In: Thirty-First AAAI Conference on Artificial Intelligence;."},{"key":"pone.0302234.ref002","doi-asserted-by":"crossref","unstructured":"Xiong B, Grauman K. Text detection in stores using a repetition prior. In: 2016 IEEE Winter Conference on Applications of Computer Vision (WACV). IEEE;. p. 1\u20139.","DOI":"10.1109\/WACV.2016.7477575"},{"issue":"7","key":"pone.0302234.ref003","doi-asserted-by":"crossref","first-page":"2972","DOI":"10.1109\/TIP.2014.2317980","article-title":"Scene text recognition in mobile applications by character descriptor and structure configuration","volume":"23","author":"C Yi","year":"2014","journal-title":"IEEE Trans Image Process"},{"issue":"7","key":"pone.0302234.ref004","doi-asserted-by":"crossref","first-page":"1480","DOI":"10.1109\/TPAMI.2014.2366765","article-title":"Text detection and recognition in imagery: A survey","volume":"37","author":"Q Ye","year":"2014","journal-title":"IEEE transactions on pattern analysis and machine intelligence"},{"issue":"9","key":"pone.0302234.ref005","doi-asserted-by":"crossref","first-page":"2035","DOI":"10.1109\/TPAMI.2018.2848939","article-title":"Aster: An attentional scene text recognizer with flexible rectification","volume":"41","author":"B Shi","year":"2018","journal-title":"IEEE transactions on pattern analysis and machine intelligence"},{"key":"pone.0302234.ref006","unstructured":"Liu Y, Chen H, Shen C, He T, Jin L, Wang L. Abcnet: Real-time scene text spotting with adaptive bezier-curve network. In: proceedings of the IEEE\/CVF conference on computer vision and pattern recognition;. p. 9809\u20139818."},{"key":"pone.0302234.ref007","doi-asserted-by":"crossref","unstructured":"Tian Z, Huang W, He T, He P, Qiao Y. Detecting text in natural image with connectionist text proposal network. In: Computer Vision\u2013ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part VIII 14. Springer;. p. 56\u201372.","DOI":"10.1007\/978-3-319-46484-8_4"},{"issue":"3","key":"pone.0302234.ref008","doi-asserted-by":"crossref","first-page":"888","DOI":"10.3390\/s21030888","article-title":"R-YOLO: A real-time text detector for natural scenes with arbitrary rotation","volume":"21","author":"X Wang","year":"2021","journal-title":"Sensors"},{"key":"pone.0302234.ref009","unstructured":"Li C, Li L, Jiang H, Weng K, Geng Y, Li L, et al. YOLOv6: A single-stage object detection framework for industrial applications. arXiv preprint arXiv:220902976. 2022;."},{"key":"pone.0302234.ref010","unstructured":"Wang W, Xie E, Song X, Zang Y, Wang W, Lu T, et al. Efficient and accurate arbitrary-shaped text detection with pixel aggregation network. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision;. p. 8440\u20138449."},{"key":"pone.0302234.ref011","unstructured":"Lin TY, Doll\u00e1r P, Girshick R, He K, Hariharan B, Belongie S. Feature pyramid networks for object detection. In: Proceedings of the IEEE conference on computer vision and pattern recognition;. p. 2117\u20132125."},{"key":"pone.0302234.ref012","unstructured":"Bochkovskiy A, Wang CY, Liao HYM. Yolov4: Optimal speed and accuracy of object detection. arXiv preprint arXiv:200410934. 2020;."},{"key":"pone.0302234.ref013","unstructured":"Glenn J. type [; 2022]Available from: https:\/\/github.com\/ultralytics\/yolov5\/releases\/tag\/v6.1."},{"key":"pone.0302234.ref014","unstructured":"Liu S, Qi L, Qin H, Shi J, Jia J. Path aggregation network for instance segmentation. In: Proceedings of the IEEE conference on computer vision and pattern recognition;. p. 8759\u20138768."},{"key":"pone.0302234.ref015","unstructured":"Ding X, Zhang X, Ma N, Han J, Ding G, Sun J. Repvgg: Making vgg-style convnets great again. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition;. p. 13733\u201313742."},{"issue":"13","key":"pone.0302234.ref016","doi-asserted-by":"crossref","first-page":"7723","DOI":"10.1007\/s00521-020-05514-1","article-title":"Spectrum interference-based two-level data augmentation method in deep learning for automatic modulation classification","volume":"33","author":"Q Zheng","year":"2021","journal-title":"Neural Computing and Applications"},{"key":"pone.0302234.ref017","doi-asserted-by":"crossref","DOI":"10.1002\/int.22586","article-title":"MR\u2010DCAE: Manifold regularization\u2010based deep convolutional autoencoder for unauthorized broadcasting identification","volume":"36","author":"Q Zheng","year":"2021","journal-title":"International Journal of Intelligent Systems"},{"issue":"6","key":"pone.0302234.ref018","doi-asserted-by":"crossref","first-page":"1298","DOI":"10.1109\/LCOMM.2022.3145647","article-title":"Fine-Grained Modulation Classification Using Multi-Scale Radio Transformer With Dual-Channel Representation","volume":"26","author":"Q Zheng","year":"2022","journal-title":"IEEE Communications Letters"},{"key":"pone.0302234.ref019","doi-asserted-by":"crossref","first-page":"104486","DOI":"10.1016\/j.scs.2023.104486","article-title":"Application of wavelet-packet transform driven deep learning method in PM2.5 concentration prediction: A case study of Qingdao, China","volume":"92","author":"Q Zheng","year":"2023","journal-title":"Sustainable Cities and Society"},{"key":"pone.0302234.ref020","doi-asserted-by":"crossref","first-page":"106082","DOI":"10.1016\/j.engappai.2023.106082","article-title":"DL-PR: Generalized automatic modulation classification method based on deep learning with priori regularization","volume":"122","author":"Q Zheng","year":"2023","journal-title":"Engineering Applications of Artificial Intelligence"},{"key":"pone.0302234.ref021","unstructured":"Liu Y, Jin L. Deep matching prior network: Toward tighter multi-oriented text detection. In: Proceedings of the IEEE conference on computer vision and pattern recognition;. p. 1962\u20131969."},{"key":"pone.0302234.ref022","unstructured":"Zhou X, Yao C, Wen H, Wang Y, Zhou S, He W, et al. East: an efficient and accurate scene text detector. In: Proceedings of the IEEE conference on Computer Vision and Pattern Recognition;. p. 5551\u20135560."},{"key":"pone.0302234.ref023","unstructured":"Kim KH, Hong S, Roh B, Cheon Y, Park M. Pvanet: Deep but lightweight neural networks for real-time object detection. arXiv preprint arXiv:160808021. 2016;."},{"key":"pone.0302234.ref024","doi-asserted-by":"crossref","unstructured":"Zhang S, Liu Y, Jin L, Luo C. Feature enhancement network: A refined scene text detector. In: Proceedings of the AAAI Conference on Artificial Intelligence. vol. 32;.","DOI":"10.1609\/aaai.v32i1.11887"},{"key":"pone.0302234.ref025","unstructured":"Liao M, Shi B, Bai X, Wang X, Liu W. Textboxes: A fast text detector with a single deep neural network. In: Thirty-first AAAI conference on artificial intelligence;."},{"issue":"8","key":"pone.0302234.ref026","doi-asserted-by":"crossref","first-page":"3676","DOI":"10.1109\/TIP.2018.2825107","article-title":"Textboxes++: A single-shot oriented scene text detector","volume":"27","author":"M Liao","year":"2018","journal-title":"IEEE transactions on image processing"},{"key":"pone.0302234.ref027","unstructured":"Qian Y, Chen L, Su F. An Adaptive Rectification Model for Arbitrary-Shaped Scene Text Recognition. 2021;."},{"key":"pone.0302234.ref028","doi-asserted-by":"crossref","unstructured":"Raisi Z, Younes G, Zelek J. Arbitrary shape text detection using transformers. In: 2022 26th International Conference on Pattern Recognition (ICPR). IEEE;. p. 3238\u20133245.","DOI":"10.1109\/ICPR56361.2022.9956488"},{"key":"pone.0302234.ref029","unstructured":"Tang J, Zhang W, Liu H, Yang M, Jiang B, Hu G, et al. Few could be better than all: Feature sampling and grouping for scene text detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition;. p. 4563\u20134572."},{"key":"pone.0302234.ref030","doi-asserted-by":"crossref","unstructured":"Deng D, Liu H, Li X, Cai D. Pixellink: Detecting scene text via instance segmentation. In: Proceedings of the AAAI Conference on Artificial Intelligence. vol. 32;.","DOI":"10.1609\/aaai.v32i1.12269"},{"key":"pone.0302234.ref031","unstructured":"Long S, Ruan J, Zhang W, He X, Wu W, Yao C. Textsnake: A flexible representation for detecting text of arbitrary shapes. In: Proceedings of the European conference on computer vision (ECCV);. p. 20\u201336."},{"key":"pone.0302234.ref032","unstructured":"Feng W, He W, Yin F, Zhang XY, Liu CL. Textdragon: An end-to-end framework for arbitrary shaped text spotting. In: Proceedings of the IEEE\/CVF international conference on computer vision;. p. 9076\u20139085."},{"key":"pone.0302234.ref033","doi-asserted-by":"crossref","unstructured":"Liao M, Wan Z, Yao C, Chen K, Bai X. Real-time scene text detection with differentiable binarization. In: Proceedings of the AAAI conference on artificial intelligence. vol. 34;. p. 11474\u201311481.","DOI":"10.1609\/aaai.v34i07.6812"},{"key":"pone.0302234.ref034","doi-asserted-by":"crossref","unstructured":"Dai Y, Huang Z, Gao Y, Xu Y, Chen K, Guo J, et al. Fused text segmentation networks for multi-oriented scene text detection. In: 2018 24th international conference on pattern recognition (ICPR). IEEE;. p. 3604\u20133609.","DOI":"10.1109\/ICPR.2018.8546066"},{"key":"pone.0302234.ref035","unstructured":"Tian Z, Shu M, Lyu P, Li R, Zhou C, Shen X, et al. Learning shape-aware embedding for scene text detection. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition;. p. 4234\u20134243."},{"key":"pone.0302234.ref036","unstructured":"Wang W, Xie E, Li X, Hou W, Lu T, Yu G, et al. Shape robust text detection with progressive scale expansion network. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition;. p. 9336\u20139345."},{"key":"pone.0302234.ref037","unstructured":"Wang CY, Liao HYM, Wu YH, Chen PY, Hsieh JW, Yeh IH. CSPNet: A new backbone that can enhance learning capability of CNN. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition workshops;. p. 390\u2013391."},{"key":"pone.0302234.ref038","unstructured":"Song G, Liu Y, Wang X. Revisiting the sibling head in object detector. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition;. p. 11563\u201311572."},{"key":"pone.0302234.ref039","unstructured":"Wu Y, Chen Y, Yuan L, Liu Z, Wang L, Li H, et al. Rethinking classification and localization for object detection. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition;. p. 10186\u201310195."},{"key":"pone.0302234.ref040","unstructured":"Ge Z, Liu S, Wang F, Li Z, Sun J. Yolox: Exceeding yolo series in 2021. arXiv preprint arXiv:210708430. 2021;."},{"key":"pone.0302234.ref041","unstructured":"Tian Z, Shen C, Chen H, He T. Fcos: Fully convolutional one-stage object detection. In: Proceedings of the IEEE\/CVF international conference on computer vision;. p. 9627\u20139636."},{"key":"pone.0302234.ref042","doi-asserted-by":"crossref","unstructured":"Li X, Sun X, Meng Y, Liang J, Wu F, Li J. Dice loss for data-imbalanced NLP tasks. arXiv preprint arXiv:191102855. 2019;.","DOI":"10.18653\/v1\/2020.acl-main.45"},{"key":"pone.0302234.ref043","unstructured":"Lin TY, Goyal P, Girshick R, He K, Doll\u00e1r P. Focal loss for dense object detection. In: Proceedings of the IEEE international conference on computer vision;. p. 2980\u20132988."},{"key":"pone.0302234.ref044","unstructured":"Shrivastava A, Gupta A, Girshick R. Training region-based object detectors with online hard example mining. In: Proceedings of the IEEE conference on computer vision and pattern recognition;. p. 761\u2013769."},{"key":"pone.0302234.ref045","doi-asserted-by":"crossref","unstructured":"Gupta A, Vedaldi A, Zisserman A. Synthetic data for text localisation in natural images. In: Proceedings of the IEEE conference on computer vision and pattern recognition;. p. 2315\u20132324.","DOI":"10.1109\/CVPR.2016.254"},{"key":"pone.0302234.ref046","doi-asserted-by":"crossref","unstructured":"Ch\u2019ng CK, Chan CS. Total-text: A comprehensive dataset for scene text detection and recognition. In: 2017 14th IAPR international conference on document analysis and recognition (ICDAR). vol. 1. IEEE;. p. 935\u2013942.","DOI":"10.1109\/ICDAR.2017.157"},{"key":"pone.0302234.ref047","unstructured":"Yuliang L, Lianwen J, Shuaitao Z, Sheng Z. Detecting curve text in the wild: New dataset and new solution. arXiv preprint arXiv:171202170. 2017;."},{"key":"pone.0302234.ref048","unstructured":"Yao C, Bai X, Liu W, Ma Y, Tu Z. Detecting texts of arbitrary orientations in natural images. In: 2012 IEEE conference on computer vision and pattern recognition. IEEE;. p. 1083\u20131090."},{"key":"pone.0302234.ref049","doi-asserted-by":"crossref","unstructured":"Karatzas D, Gomez-Bigorda L, Nicolaou A, Ghosh S, Bagdanov A, Iwamura M, et al. ICDAR 2015 competition on robust reading. In: 2015 13th international conference on document analysis and recognition (ICDAR). IEEE;. p. 1156\u20131160.","DOI":"10.1109\/ICDAR.2015.7333942"},{"key":"pone.0302234.ref050","unstructured":"Kingma DP, Ba J. Adam: A method for stochastic optimization. arXiv preprint arXiv:14126980. 2014;."},{"key":"pone.0302234.ref051","unstructured":"Zhao H, Shi J, Qi X, Wang X, Jia J. Pyramid scene parsing network. In: Proceedings of the IEEE conference on computer vision and pattern recognition;. p. 2881\u20132890."},{"key":"pone.0302234.ref052","unstructured":"Li H, Wang P, Shen C. Towards end-to-end text spotting with convolutional recurrent neural networks. In: Proceedings of the IEEE international conference on computer vision;. p. 5238\u20135246."},{"key":"pone.0302234.ref053","unstructured":"Shi B, Bai X, Belongie S. Detecting oriented text in natural images by linking segments. In: Proceedings of the IEEE conference on computer vision and pattern recognition;. p. 2550\u20132558."},{"issue":"11","key":"pone.0302234.ref054","doi-asserted-by":"crossref","first-page":"3111","DOI":"10.1109\/TMM.2018.2818020","article-title":"Arbitrary-oriented scene text detection via rotation proposals","volume":"20","author":"J Ma","year":"2018","journal-title":"IEEE transactions on multimedia"},{"key":"pone.0302234.ref055","unstructured":"Noh H, Hong S, Han B. Learning deconvolution network for semantic segmentation. In: Proceedings of the IEEE international conference on computer vision;. p. 1520\u20131528."},{"issue":"9","key":"pone.0302234.ref056","first-page":"5349","article-title":"Pan++: Towards efficient and accurate end-to-end spotting of arbitrarily-shaped text","volume":"44","author":"W Wang","year":"2021","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"pone.0302234.ref057","doi-asserted-by":"crossref","unstructured":"Liu X, Liang D, Yan S, Chen D, Qiao Y, Yan J. Fots: Fast oriented text spotting with a unified network. In: Proceedings of the IEEE conference on computer vision and pattern recognition;. p. 5676\u20135685.","DOI":"10.1109\/CVPR.2018.00595"},{"key":"pone.0302234.ref058","unstructured":"Zhang C, Liang B, Huang Z, En M, Han J, Ding E, et al. Look more than once: An accurate detector for text of arbitrary shapes. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition;. p. 10552\u201310561."},{"key":"pone.0302234.ref059","unstructured":"Baek Y, Lee B, Han D, Yun S, Lee H. Character region awareness for text detection. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition;. p. 9365\u20139374."},{"key":"pone.0302234.ref060","doi-asserted-by":"crossref","unstructured":"He W, Zhang XY, Yin F, Liu CL. Deep direct regression for multi-oriented scene text detection. In: Proceedings of the IEEE international conference on computer vision;. p. 745\u2013753.","DOI":"10.1109\/ICCV.2017.87"},{"key":"pone.0302234.ref061","unstructured":"He P, Huang W, He T, Zhu Q, Qiao Y, Li X. Single shot text detector with regional attention. In: Proceedings of the IEEE international conference on computer vision;. p. 3047\u20133055."},{"key":"pone.0302234.ref062","unstructured":"Hu H, Zhang C, Luo Y, Wang Y, Han J, Ding E. Wordsup: Exploiting word annotations for character based text detection. In: Proceedings of the IEEE international conference on computer vision;. p. 4940\u20134949."},{"key":"pone.0302234.ref063","doi-asserted-by":"crossref","unstructured":"Liu Z, Lin G, Yang S, Feng J, Lin W, Goh WL. Learning Markov Clustering Networks for Scene Text Detection. In: 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition; 2018. p. 6936\u20136944.","DOI":"10.1109\/CVPR.2018.00725"}],"container-title":["PLOS ONE"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pone.0302234","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,16]],"date-time":"2024-11-16T10:54:11Z","timestamp":1731754451000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pone.0302234"}},"subtitle":[],"editor":[{"given":"Feng","family":"Ding","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2024,4,16]]},"references-count":63,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2024,4,16]]}},"URL":"https:\/\/doi.org\/10.1371\/journal.pone.0302234","relation":{},"ISSN":["1932-6203"],"issn-type":[{"value":"1932-6203","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,4,16]]}}}