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Deformable scene text detection using harmonic features and modified pixel aggregation network

文献类型：期刊论文

作者Jain, Tanmay2; Palaiahnakote, Shivakumara1; Pal, Umapada2; Liu, Cheng-Lin3,4
刊名PATTERN RECOGNITION LETTERS
出版日期2021-12-01
卷号152页码:135-142
关键词Natural scene text detection Maximally stable extremal region Fourier harmonic features Pixel aggregation network Deep learning models Deformable text detection
ISSN号0167-8655
DOI10.1016/j.patrec.2021.10.006
通讯作者Palaiahnakote, Shivakumara(shiva@um.edu.my)
英文摘要Although text detection methods have addressed several challenges in the past, there is a dearth of effective methods for text detection in deformable images, such as images containing text embedded on cloth, banners, rubber, sports jerseys, uniforms, etc. This is because deformable regions contain surfaces of arbitrarily shapes, which lead to poor text quality. This paper presents a new method for deformable text detection in natural scene images. It is observed that although the shapes of characters change in a deformable region, the pixel values and spatial relationship between the pixels do not change. This motivated us to explore extraction of Maximally Stable Extremal Regions (MSER) in an image in which pixels that share common features are grouped into components. The unique character shape variations led us to explore harmonic features to represent the component shape variations, using which a classifier classifies text and non-text components from the output of the MSER step. Additionally, the objective of developing a lightweight method with low computational cost motivated us to introduce a modified Pixel Aggression Network (PAN) for text deformable text detection at a component level. Comprehensive experiments which include experiments on our Deformable Text Dataset (DTD) and standard natural scene text datasets, namely, MSRATD-500, ICDAR 2019 MLT, Total-Text, CTW1500, ICDAR 2019 ArT and DSTA1500 datasets show that the proposed model outperforms the existing methods for our dataset as well as the standard datasets. (c) 2021 Elsevier B.V. All rights reserved.
资助项目FRGS grant, Ministry of Higher Education, Malaysia[FP1042020] ; TIH, ISI, Kolkata
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000711455600007
出版者ELSEVIER
资助机构FRGS grant, Ministry of Higher Education, Malaysia ; TIH, ISI, Kolkata
源URL[http://ir.ia.ac.cn/handle/173211/46273]  
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Palaiahnakote, Shivakumara
作者单位1.Univ Malaya, Fac Comp Sci & Informat Technol, Dept Comp Syst & Technol, Kuala Lumpur, Malaysia
2.Indian Stat Inst, Comp Vis & Pattern Recognit Unit, Kolkata, India
3.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
4.Chinese Acad Sci, Inst Automat, Cheng Lin Liu Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Jain, Tanmay,Palaiahnakote, Shivakumara,Pal, Umapada,et al. Deformable scene text detection using harmonic features and modified pixel aggregation network[J]. PATTERN RECOGNITION LETTERS,2021,152:135-142.
APA Jain, Tanmay,Palaiahnakote, Shivakumara,Pal, Umapada,&Liu, Cheng-Lin.(2021).Deformable scene text detection using harmonic features and modified pixel aggregation network.PATTERN RECOGNITION LETTERS,152,135-142.
MLA Jain, Tanmay,et al."Deformable scene text detection using harmonic features and modified pixel aggregation network".PATTERN RECOGNITION LETTERS 152(2021):135-142.

入库方式： OAI收割

来源：自动化研究所

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