Development of Vertical Text Interpreter for Natural Scene Images
Automatic text recognition in natural scene images is essential for accessing information and understanding our surroundings. Scene text orientations include horizontal scene texts, arbitrarily oriented scene texts, curved scene texts, and vertically oriented scene texts. While attention has been gi...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2021-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9580909/ |
| _version_ | 1818837136978214912 |
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| author | Ong Yi Ling Lau Bee Theng Almon Chai Weiyen Christopher Mccarthy |
| author_facet | Ong Yi Ling Lau Bee Theng Almon Chai Weiyen Christopher Mccarthy |
| author_sort | Ong Yi Ling |
| collection | DOAJ |
| description | Automatic text recognition in natural scene images is essential for accessing information and understanding our surroundings. Scene text orientations include horizontal scene texts, arbitrarily oriented scene texts, curved scene texts, and vertically oriented scene texts. While attention has been given to horizontal, arbitrarily oriented, and curved text, limited research has been carried out on vertically oriented scene text recognition. To this end, we propose Vertical Text Interpreter, an autonomous vertically oriented scene text recognizer model. Vertical Text Interpreter detects and recognizes vertically oriented scene texts in natural scenes, including vertically-stacked texts, bottom-to-top vertical texts, and top-to-bottom vertical texts. It consists of a shared convolutional neural network, a Vertical Text Spotter, and a Vertical Text Reader. We developed a dataset, namely Vertically Oriented Scene Text 1250 Dataset, created as part of this research, addressing the need for a dataset for this category of scene texts. The performance of the Vertical Text Interpreter is evaluated using benchmark datasets and the VOST-1250 dataset. Results show that Vertical Text Interpreter can detect and recognize different types of vertically oriented scene texts simultaneously. For future work, we can explore Vertical Text Interpreter for the contexts such as reading assistance and visual navigation systems. |
| first_indexed | 2024-12-19T03:17:43Z |
| format | Article |
| id | doaj.art-35cbd862fb13404c9f4c024f90235616 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-19T03:17:43Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-35cbd862fb13404c9f4c024f902356162022-12-21T20:37:51ZengIEEEIEEE Access2169-35362021-01-01914434114435110.1109/ACCESS.2021.31216089580909Development of Vertical Text Interpreter for Natural Scene ImagesOng Yi Ling0https://orcid.org/0000-0003-3728-1187Lau Bee Theng1Almon Chai Weiyen2Christopher Mccarthy3https://orcid.org/0000-0003-3848-1631Faculty of Engineering, Computing, and Science, Swinburne University of Technology Sarawak Campus, Kuching, Sarawak, MalaysiaFaculty of Engineering, Computing, and Science, Swinburne University of Technology Sarawak Campus, Kuching, Sarawak, MalaysiaFaculty of Engineering, Computing, and Science, Swinburne University of Technology Sarawak Campus, Kuching, Sarawak, MalaysiaFaculty of Science, Engineering and Technology, Swinburne University of Technology, Melbourne, VIC, AustraliaAutomatic text recognition in natural scene images is essential for accessing information and understanding our surroundings. Scene text orientations include horizontal scene texts, arbitrarily oriented scene texts, curved scene texts, and vertically oriented scene texts. While attention has been given to horizontal, arbitrarily oriented, and curved text, limited research has been carried out on vertically oriented scene text recognition. To this end, we propose Vertical Text Interpreter, an autonomous vertically oriented scene text recognizer model. Vertical Text Interpreter detects and recognizes vertically oriented scene texts in natural scenes, including vertically-stacked texts, bottom-to-top vertical texts, and top-to-bottom vertical texts. It consists of a shared convolutional neural network, a Vertical Text Spotter, and a Vertical Text Reader. We developed a dataset, namely Vertically Oriented Scene Text 1250 Dataset, created as part of this research, addressing the need for a dataset for this category of scene texts. The performance of the Vertical Text Interpreter is evaluated using benchmark datasets and the VOST-1250 dataset. Results show that Vertical Text Interpreter can detect and recognize different types of vertically oriented scene texts simultaneously. For future work, we can explore Vertical Text Interpreter for the contexts such as reading assistance and visual navigation systems.https://ieeexplore.ieee.org/document/9580909/Deep learningscene text detectionscene text recognitionshared convolutionvertical text interpreter |
| spellingShingle | Ong Yi Ling Lau Bee Theng Almon Chai Weiyen Christopher Mccarthy Development of Vertical Text Interpreter for Natural Scene Images IEEE Access Deep learning scene text detection scene text recognition shared convolution vertical text interpreter |
| title | Development of Vertical Text Interpreter for Natural Scene Images |
| title_full | Development of Vertical Text Interpreter for Natural Scene Images |
| title_fullStr | Development of Vertical Text Interpreter for Natural Scene Images |
| title_full_unstemmed | Development of Vertical Text Interpreter for Natural Scene Images |
| title_short | Development of Vertical Text Interpreter for Natural Scene Images |
| title_sort | development of vertical text interpreter for natural scene images |
| topic | Deep learning scene text detection scene text recognition shared convolution vertical text interpreter |
| url | https://ieeexplore.ieee.org/document/9580909/ |
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