Abstract
As demand grows for mobile phone applications, research in optical character recognition, a technology well developed for scanned documents, is shifting focus to the recognition of text embedded in digital photographs. In this paper, we present OCRdroid, a generic framework for developing OCR-based applications on mobile phones. OCRdroid combines a light-weight image preprocessing suite installed inside the mobile phone and an OCR engine connected to a backend server. We demonstrate the power and functionality of this framework by implementing two applications called PocketPal and PocketReader based on OCRdroid on HTC Android G1 mobile phone. Initial evaluations of these pilot experiments demonstrate the potential of using OCRdroid framework for real-world OCR-based mobile applications.
This work was supported in part by NSF grant CCR-0120778 (CENS: Center for Embedded Networked Sensing), and by a gift from the Okawa Foundation.
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References
ABBYY Mobile OCR Engine, http://www.abbyy.com/mobileocr/
GOCR - A Free Optical Character Recognition Program, http://jocr.sourceforge.net/
OCR resources (OCRopus), http://sites.google.com/site/ocropus/ocr-resources
OCRAD - The GNU OCR, http://www.gnu.org/software/ocrad/
OCRdroid, http://www-scf.usc.edu/~ananddjo/ocrdroid/index.php
Simple OCR - Optical Character Recognition, http://www.simpleocr.com/
Tesseract OCR Engine, http://code.google.com/p/tesseract-ocr/
Visual Codes, http://www.vs.inf.ethz.ch/res/show.html?what=visualcodes
WINTONE Mobile OCR Engine, http://www.wintone.com.cn/en/prod/44/detail270.aspx
Bieniecki, W., Grabowski, S., Rozenberg, W.: Image preprocessing for improving ocr accuracy. In: Perspective Technologies and Methods in MEMS Design, MEMSTECH 2007 (2007)
Bruns, E., Bimber, O.: Adaptive training of video sets for image recognition on mobile phones (2009)
Chen, X., Yang, J., Zhang, J., Waibel, A.: Automatic detection and recognition of signs from natural scenes (2004)
Elmore, M., Martonosi, M.: A morphological image preprocessing suite for ocr on natural scene images (2008)
Liang, J., Doermann, D., Li, H.P.: Camera-based analysis of text and documents: a survey. International Journal on Document Analysis and Recognition 7(2-3), 84–104 (2005)
Luo, X.P., Li, J., Zhen, L.X.: Design and implementation of a card reader based on build-in camera. In: ICPR 2004: Proceedings of the Pattern Recognition, 17th International Conference on (ICPR 2004), vol. 1, pp. I: 417–420. IEEE Computer Society, Los Alamitos (2004)
Mistry, P., Maes, P.: Quickies: Intelligent sticky notes. In: International Conference on Intelligent Environments (2008)
Niblack, W.: An Introduction to Digital Image Processing. Prentice-Hall, Englewood Cliffs (1986)
Ohbuchi, E., Hanaizumi, H., Hock, L.A.: Barcode readers using the camera device in mobile phones. In: CW 2004: Proceedings of the 2004 International Conference on Cyberworlds, pp. 260–265. IEEE Computer Society, Los Alamitos (2004)
Otsu, N.: A threshold selection method from gray-level histograms. IEEE Transactions on Systems, Man and Cybernetics 9(1), 62–66 (1979)
Rice, S.V., Jenkins, F.R., Nartker, T.A.: OCR accuracy: UNLV’s fifth annual test. INFORM, 10, xx–yy (1996)
Sauvola, J., Pietikainen, M.: Adaptive document image binarization. Pattern Recognition 33(2), 225–236 (2000)
Seeger, M., Dance, C.: Binarising camera images for OCR. In: Sixth International Conference on Document Analysis and Recognition (ICDAR 2001), pp. 54–58 (2001)
Sezgin, M., Sankur, B.: Survey over image thresholding techniques and quantitative performance evaluation. Journal of Electronic Imaging 13(1), 146–168 (2004)
Shafait, F., Keysers, D., Breuel, T.M.: Efficient implementation of local adaptive thresholding techniques using integral images. In: Document Recognition and Retrieval XV, vol. 6815, 681510 (2008)
Ulges, A., Lampert, C.H., Breuel, T.M.: Document image dewarping using robust estimation of curled text lines. In: Eighth International Conference on Document Analysis and Recognition, pp. II: 1001–1005 (2005)
Whitesell, K., Kutler, B., Ramanathan, N., Estrin, D.: A system determining indoor air quality from images air sensor captured cell phones (2008)
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Zhang, M., Joshi, A., Kadmawala, R., Dantu, K., Poduri, S., Sukhatme, G.S. (2010). OCRdroid: A Framework to Digitize Text Using Mobile Phones. In: Phan, T., Montanari, R., Zerfos, P. (eds) Mobile Computing, Applications, and Services. MobiCASE 2009. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 35. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12607-9_18
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DOI: https://doi.org/10.1007/978-3-642-12607-9_18
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