Raghunandan, K.S. and Shivakumara, Palaiahnakote and Roy, Sangheeta and Kumar, Govindaraj Hemantha and Pal, Umapada and Lu, Tong (2019) Multi-Script-Oriented Text Detection and Recognition in Video/Scene/Born Digital Images. IEEE Transactions on Circuits and Systems for Video Technology, 29 (4). pp. 1145-1162. ISSN 1051-8215, DOI https://doi.org/10.1109/TCSVT.2018.2817642.
Full text not available from this repository.Abstract
Achieving good text detection and recognition results for multi-script-oriented images is a challenging task. First, we explore bit plane slicing in order to utilize the advantage of the most significant bit information to identify text components. A new iterative nearest neighbor symmetry is then proposed based on shapes of convex and concave deficiencies of text components in bit planes to identify candidate planes. Further, we introduce a new concept called mutual nearest neighbor pair components based on gradient direction to identify representative pairs of texts in each candidate bit plane. The representative pairs are used to restore words with the help of edge image of the input one, which results in text detection results (words). Second, we propose a new idea by fixing window for character components of arbitrary oriented words based on angular relationship between sub-bands and a fused band. For each window, we extract features in contourlet wavelet domain to detect characters with the help of an SVM classifier. Further, we propose to explore HMM for recognizing characters and words of any orientation using the same feature vector. The proposed method is evaluated on standard databases such as ICDAR, YVT video, ICDAR, SVT, MSRA scene data, ICDAR born digital data, and multi-lingual data to show its superiority to the state of the art methods. © 1991-2012 IEEE.
| Item Type: | Article |
|---|---|
| Funders: | Natural Science Foundation of China under Grant 61672273, Grant 61272218, and Grant 61321491, Science Foundation for Distinguished Young Scholars of Jiangsu under Grant BK20160021 |
| Uncontrolled Keywords: | arbitrarily-oriented text detection and recognition; Bit plane slicing; convex and concave deficiencies; hidden Markov model; multi-lingual text detection and recognition; wavelet sub-bands |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Faculty of Computer Science & Information Technology |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 10 Feb 2020 06:37 |
| Last Modified: | 10 Feb 2020 06:37 |
| URI: | http://eprints.um.edu.my/id/eprint/23712 |
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