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Fast Photo Time-Stamp Recognition Based on SGNN

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Advances in Neural Networks - ISNN 2006 (ISNN 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3972))

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Abstract

Photo time-stamp is a valuable information source for content-based retrieval of scanned photo databases. A fast photo-stamp recognizing approach based on Self-Generating Neural Networks (SGNN) is proposed in this paper. Network structures and parameters of SGNN needn’t to be set by users, and their learning process needn’t iteration, so SGNN can be trained on-line. Proposed method consists of three steps: A photo is roughly segmented to determine which corner of the photo contains time-stamp; The area which contains time-stamp of the photo is finely segmented, in order to locate each character in the time-stamp, projection technology is used to locate edges of these characters; The time-stamp is recognized based on SGNN. Experimental results show that proposed approach can achieve higher recognition accuracy and computing efficiency.

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References

  • Lienhart, A., Wernicke, A.: Localizing and Segmenting Text in Images and Videos. IEEE Transactions on Circuits and Systems for Video Technology 12(4), 256–268 (2002)

    Article  Google Scholar 

  • Yin, P., Hua, X.S., Zhang, H.J.: Automatic Time Stamp Extraction System for Home Videos. In: Proc. of IEEE Int. Symp. on Circuits and Systems, pp. 73–76. IEEE, New York (2002)

    Google Scholar 

  • Chen, X., Zhang, H.: Photo Time-Stamp Detection and Recognition. In: Proc. of Int. Conf. on Document Analysis and Recognition, pp. 319–322. IEEE Computer Society, Los Alamitos (2003)

    Google Scholar 

  • Bao, F.M., Li, A.G., Qin, Z.: Photo Time-Stamp Recognition Based on Particle Swarm Optimization. In: Zhong, N., Tirri, H., Yao, Y., et al. (eds.) Proc. of IEEE/Wic/ACM Int. Conf. on Web Intelligence, pp. 529–532. IEEE Computer Society, Los Alamitos (2004)

    Google Scholar 

  • Wen, W.X., Jennings, A., Liu, H.: Learning A Neural Tree. In: Proc. of Int. Joint Conf. on Neural Networks, Beijing, China, pp. 751–756 (1992)

    Google Scholar 

  • Qin, Z., Bao, F.M., Li, A.G.: A Novel Image Fusion Method Based on SGNN. In: Wang, J., Liao, X.-F., Yi, Z. (eds.) ISNN 2005. LNCS, vol. 3497, pp. 747–752. Springer, Heidelberg (2005)

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Author information

Authors and Affiliations

  1. Department of Computer Science and Technology, Xi’an University of Science and Technology, 710054, Xi’an, China

    Aiguo Li

Authors
  1. Aiguo Li
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Editor information

Editors and Affiliations

  1. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  2. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

  3. Department of Electrical Engineering, University of Louisville, 40292, Louisville, KY, U.S.A

    Jacek M. Zurada

  4. Laboratory for Computational Biology, Shanghai Center for Systems Biomedicine, 800 Dong Chuan Rd., 200240, Shanghai, China

    Bao-Liang Lu

  5. School of Electrical and Electronic Engineering, University of Manchester, UK

    Hujun Yin

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© 2006 Springer-Verlag Berlin Heidelberg

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Li, A. (2006). Fast Photo Time-Stamp Recognition Based on SGNN. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3972. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760023_46

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  • DOI: https://doi.org/10.1007/11760023_46

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34437-7

  • Online ISBN: 978-3-540-34438-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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