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International Journal on Document Analysis and Recognition (IJDAR)
Erschienen in: International Journal on Document Analysis and Recognition (IJDAR) 1/2020

01.08.2019 | Original Paper

Total-Text: toward orientation robustness in scene text detection

verfasst von: Chee-Kheng Ch’ng, Chee Seng Chan, Cheng-Lin Liu

Erschienen in: International Journal on Document Analysis and Recognition (IJDAR) | Ausgabe 1/2020

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Abstract

At present, text orientation is not diverse enough in the existing scene text datasets. Specifically, curve-orientated text is largely out-numbered by horizontal and multi-oriented text, hence, it has received minimal attention from the community so far. Motivated by this phenomenon, we collected a new scene text dataset, Total-Text, which emphasized on text orientations diversity. It is the first relatively large scale scene text dataset that features three different text orientations: horizontal, multi-oriented, and curve-oriented. In addition, we also study several other important elements such as the practicality and quality of ground truth, evaluation protocol, and the annotation process. We believe that these elements are as important as the images and ground truth to facilitate a new research direction. Secondly, we propose a new scene text detection model as the baseline for Total-Text, namely Polygon-Faster-RCNN, and demonstrated its ability to detect text of all orientations. Images of Total-Text and its annotation are available at https://​github.​com/​cs-chan/​Total-Text-Dataset.
Vorheriger Artikel Document analysis systems that improve with use
Nächster Artikel A unified method for augmented incremental recognition of online handwritten Japanese and English text

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Fußnoten
1
This is achieved by ‘colorThreshold’ function in MATLAB.
 
4
It is sufficient to cover most of the text regions in Total-Text but not texts with larger curvature. Examples in Fig. 21.
 
5
Apart from CUTE80 and CTW1500, which we used the model fine-tuned on Total-Text only.
 
6
The new ground truths will be released in the same GitHub page as well.
 
7
Credit to Baidu Inc. who helped in re-annotating the ground truth in such format. We (the authors of CTW1500 and us) reached a common ground that Latin scripts should be annotated in word level while Chinese scripts should be annotated in line level due to the nature of both languages.
 
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Metadaten
Titel
Total-Text: toward orientation robustness in scene text detection
verfasst von
Chee-Kheng Ch’ng
Chee Seng Chan
Cheng-Lin Liu
Publikationsdatum
01.08.2019
Verlag
Springer Berlin Heidelberg
Erschienen in
International Journal on Document Analysis and Recognition (IJDAR) / Ausgabe 1/2020
Print ISSN: 1433-2833
Elektronische ISSN: 1433-2825
DOI
https://doi.org/10.1007/s10032-019-00334-z

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