Text recognition approaches for indoor robotics: a comparison
Lam, Obadiah, Dayoub, Feras, Schulz, Ruth, & Corke, Peter (2014) Text recognition approaches for indoor robotics: a comparison. In Chen, C (Ed.) Proceedings of the 16th Australasian Conference on Robotics and Automation 2014. Australian Robotics and Automation Association (ARAA), Australia, pp. 1-7.
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Description
This paper evaluates the performance of different text recognition techniques for a mobile robot in an indoor (university campus) environment. We compared four different methods: our own approach using existing text detection methods (Minimally Stable Extremal Regions detector and Stroke Width Transform) combined with a convolutional neural network, two modes of the open source program Tesseract, and the experimental mobile app Google Goggles. The results show that a convolutional neural network combined with the Stroke Width Transform gives the best performance in correctly matched text on images with single characters whereas Google Goggles gives the best performance on images with multiple words. The dataset used for this work is released as well.
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| ID Code: | 78741 | ||||
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| Item Type: | Chapter in Book, Report or Conference volume (Conference contribution) | ||||
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| Measurements or Duration: | 7 pages | ||||
| Event Title: | Australasian Conference on Robotics and Automation | ||||
| Event Dates: | 2014-12-02 - 2014-12-04 | ||||
| Event Location: | Melbourne, Australia | ||||
| Pure ID: | 32644174 | ||||
| Divisions: | Past > Institutes > Institute for Future Environments Past > QUT Faculties & Divisions > Science & Engineering Faculty Past > Schools > School of Electrical Engineering & Computer Science Current > Research Centres > ARC Centre of Excellence for Robotic Vision Current > Research Centres > Centre for Tropical Crops and Biocommodities |
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| Copyright Owner: | Consult author(s) regarding copyright matters | ||||
| Copyright Statement: | This work is covered by copyright. Unless the document is being made available under a Creative Commons Licence, you must assume that re-use is limited to personal use and that permission from the copyright owner must be obtained for all other uses. If the document is available under a Creative Commons License (or other specified license) then refer to the Licence for details of permitted re-use. It is a condition of access that users recognise and abide by the legal requirements associated with these rights. If you believe that this work infringes copyright please provide details by email to qut.copyright@qut.edu.au | ||||
| Deposited On: | 19 Nov 2014 08:58 | ||||
| Last Modified: | 31 Oct 2025 14:38 |
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