Skip to main content

Paradise Pointer : A Sightseeing Scenes Images Search Engine Based on Big Data Processing

  • Conference paper
Intelligent Computation in Big Data Era (ICYCSEE 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 503))

  • 2042 Accesses

Abstract

Nowadays, with the rapid development of network, more and more people are willing to share their attractive photos on the internet, especially the sightseeing spot photos. However, there are countless noteless but splendid scenic spots that remain unknown to most people, and it is a pity that one finds a wonderful place but cannot reach it. Therefore, it is meaningful and useful to build an image search website used specially for sightseeing spot images. Meanwhile, we have stepped into the new era of Big Data, the data we need to process is in an explosive growth, including the images. Thus we develop ParadisePointer, a scenery image search engine, which used the processing method on the background of Big Data. In this paper, we are going to introduce the main stages of our system and some key features of ParadisePointer.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. http://www.deviantart.com/

  2. Chen, C.-H., Takama, Y.: Situation-Oriented Hierarchical Classification for Sightseeing Images Based on Local Color Feature. Journal of Advanced Computational Intelligence and Intelligent Informatics 17(3), 459–468 (2013)

    Google Scholar 

  3. Gudivada, V.N., Raghavan, V.V.: Content based image retrieval systems. Computer 28(9), 18–22 (1995)

    Article  Google Scholar 

  4. Flickner, M., et al.: Query by image and video content: The QBIC system. Computer 28(9), 23–32 (1995)

    Article  Google Scholar 

  5. Liu, Y., et al.: A survey of content-based image retrieval with high-level semantics. Pattern Recognition 40(1), 262–282 (2007)

    Article  MATH  Google Scholar 

  6. Ding, L., Goshtasby, A.: On the Canny edge detector. Pattern Recognition 34(3), 721–725 (2001)

    Article  MATH  Google Scholar 

  7. http://www.attrasoft.com/oldsite/brochure.proof.FINAL3.pdf

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Pan, J., Wang, H., Gao, H., Zhao, W., Huo, H., Dong, H. (2015). Paradise Pointer : A Sightseeing Scenes Images Search Engine Based on Big Data Processing. In: Wang, H., et al. Intelligent Computation in Big Data Era. ICYCSEE 2015. Communications in Computer and Information Science, vol 503. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46248-5_54

Download citation

  • DOI: https://doi.org/10.1007/978-3-662-46248-5_54

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-46247-8

  • Online ISBN: 978-3-662-46248-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics