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A comprehensive scheme for tattoo text detection

文献类型：期刊论文

作者Banerjee, Ayan5; Shivakumara, Palaiahnakote4; Pal, Umapada5; Raghavendra, Ramachandra3; Liu, Cheng-Lin1,2
刊名PATTERN RECOGNITION LETTERS
出版日期2022-11-01
卷号163页码:168-179
ISSN号0167-8655
DOI10.1016/j.patrec.2022.10.007
通讯作者Raghavendra, Ramachandra(raghavendra.ramachandra@ntnu.no)
英文摘要Tattoo text detection provides a vital clue for person and crime identification. Due to the freestyle and unconstrained nature of handwritten tattoo text over skin regions, accurate tattoo text detection is very challenging. This paper proposes a comprehensive scheme for tattoo text detection which comprises (a) adaptive Deformable Convolutional Neural Network (DCNN) for skin region detection to reduce text detection complexity (b) a Decoupled Gradient Text Detector (DGTD) for tattoo text detection from skin region (c) a Deep Q-Network (DQN) to refine the bounding boxes detected by DGTD, and (d) a Term -Frequency-Inverse-Document-Frequency (TF-IDF) model to group the words into text lines based on se-mantic information to fix the bounding box for the line. To test the effectiveness, the proposed method is evaluated on different datasets, namely, (i) a newly developed tattoo text dataset, (ii) benchmark bib number dataset of the marathon, and (iii) person re-identification dataset. The proposed method achieves 91.2, 87.5, and 88.8 F-scores from these three respective datasets. To demonstrate its superior performance, the text detection module (without skin detection) is also compared with state-of-the-art scene text detection methods on benchmark datasets, namely, ICDAR 2019 ArT, Total-Text, and DAST1500 and the proposed method achieves 90.3, 88.5 and 89.8 F-score from these respective datasets. (c) 2022 The Authors. Published by Elsevier B.V.
WOS关键词RECOGNITION
资助项目Ministry of Higher Education of Malaysia[FRGS/1/2020/ICT02/UM/02/4] ; TIH, ISI Kolkata
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000877215000013
出版者ELSEVIER
资助机构Ministry of Higher Education of Malaysia ; TIH, ISI Kolkata
源URL[http://ir.ia.ac.cn/handle/173211/50563]  
专题自动化研究所_模式识别国家重点实验室_模式分析与学习团队
通讯作者Raghavendra, Ramachandra
作者单位1.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
2.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100190, Peoples R China
3.NTNU, Fac Informat Technol & Elect Engn, IIK, Oslo, Norway
4.Univ Malaya, Dept Comp Syst & Technol, Kula Lumpur, Malaysia
5.Indian Stat Inst, Comp Vis & Pattern Recognit Unit, Kolkata, India
推荐引用方式
GB/T 7714		 Banerjee, Ayan,Shivakumara, Palaiahnakote,Pal, Umapada,et al. A comprehensive scheme for tattoo text detection[J]. PATTERN RECOGNITION LETTERS,2022,163:168-179.
APA Banerjee, Ayan,Shivakumara, Palaiahnakote,Pal, Umapada,Raghavendra, Ramachandra,&Liu, Cheng-Lin.(2022).A comprehensive scheme for tattoo text detection.PATTERN RECOGNITION LETTERS,163,168-179.
MLA Banerjee, Ayan,et al."A comprehensive scheme for tattoo text detection".PATTERN RECOGNITION LETTERS 163(2022):168-179.

入库方式： OAI收割

来源：自动化研究所

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