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High Speed Extraction Model of ROI for Automatic Logistics System

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Neural Information Processing (ICONIP 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3316))

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Abstract

This paper deals with a model for the high-speed extraction of Region of Interest (ROI) during the process of logistics transported on conveyor belt.The objective of this paper is to extract various ROIs of the large size image of logistics more than 4,096 by 4,096. For this purpose, we propose a wavelet extension and a texture extension method, and verified it by the experiments. Our experiments show that the proposed methods extract ROIs nearly 100 percent.

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References

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Author information

Authors and Affiliations

  1. ETRI, Postal Technology Research Center, 161 Ga-jung-dong, Daejeon, 305-350, Korea

    Moon-sung Park

  2. Paichai University, 439-6 Do-ma-dong Seo-gu, Daejeon, 302-735, Korea

    Il-sook Kim

  3. Department of Computer, Internet & Information, DaeDuk College, 48 Jang-dong You-sung-gu, Daejeon, 305-715, Korea

    Eun-kyung Cho & Young-hee Kwon

Authors
  1. Moon-sung Park
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  2. Il-sook Kim
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  3. Eun-kyung Cho
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  4. Young-hee Kwon
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Editor information

Editors and Affiliations

  1. Indian Statistical Institute, Electronics and Communication Sciences Unit, Kolkata, India

    Nikhil Ranjan Pal

  2. School of Computer and Information Sciences, Knowledge Engineering and Discovery Research Institute (KEDRI), Auckland University of Technology, Private Bag 92006, Auckland, New Zealand

    Nik Kasabov

  3. Department of Instrumentation and Electronics Engineering, Jadavpur University, Salt-lake Campus, 700098, Calcutta, India

    Rajani K. Mudi

  4. Indian Statistical Institute, 203 B. T. Road, 700 108, Calcutta,  

    Srimanta Pal

  5. Indian Statistical Institute, Computer Vision and Pattern Recognition Unit, 700108, Kolkata, India

    Swapan Kumar Parui

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© 2004 Springer-Verlag Berlin Heidelberg

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Park, Ms., Kim, Is., Cho, Ek., Kwon, Yh. (2004). High Speed Extraction Model of ROI for Automatic Logistics System. In: Pal, N.R., Kasabov, N., Mudi, R.K., Pal, S., Parui, S.K. (eds) Neural Information Processing. ICONIP 2004. Lecture Notes in Computer Science, vol 3316. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30499-9_108

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  • DOI: https://doi.org/10.1007/978-3-540-30499-9_108

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23931-4

  • Online ISBN: 978-3-540-30499-9

  • eBook Packages: Springer Book Archive

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