Digital Marketing Handbook

Image search 58

• Personal Collection - usually consists of a largely homogeneous collection and is generally small in size,
  accessible primarily to its owner, and usually stored on a local storage media.


• Web - World Wide Web images are accessible to everyone with an Internet connection. These image collections
  are semi-structured, non-homogeneous and massive in volume, and are usually stored in large disk arrays.

Evaluations

There are evaluation workshops for image retrieval systems aiming to investigate and improve the performance of

such systems.

• ImageCLEF [3] - a continuing track of the Cross Language Evaluation Forum [4] that evaluates systems using both
  textual and pure-image retrieval methods.


• Content-based Access of Image and Video Libraries [5] - a series of IEEE workshops from 1998 to 2001.

References

[ 1 ]Prasad, B E; A Gupta, H-M Toong, S.E. Madnick (February 1987). "A microcomputer-based image database management system". IEEE

Transactions on Industrial Electronics IE-34 (1): 83–8. doi:10.1109/TIE.1987.350929.

[ 2 ]Datta, Ritendra; Dhiraj Joshi, Jia Li, James Z. Wang (April 2008). "Image Retrieval: Ideas, Influences, and Trends of the New Age" (http:/ /

infolab. stanford. edu/ ~wangz/ project/ imsearch/ review/ JOUR/ ). ACM Computing Surveys 40 (2): 1–60. doi:10.1145/1348246.1348248..

[ 3 ]http:/ / http://www. imageclef. org

[ 4 ]http:/ / http://www. clef-campaign. org

[ 5 ]http:/ / ieeexplore. ieee. org/ xpl/ RecentCon. jsp?punumber=4980

External links

• microsoft.com (http:/ / research. microsoft. com/ en-us/ um/ people/ larryz/ zitnickcfir03. pdf), Content-Free
  Image Retrieval by C. Lawrence Zitnick and Takeo Kanade, May 2003


• PDF (http:/ / http://www. asis. org/ Bulletin/ Jun-09/ JunJul09_Uzwyshyn. pdf) Bulletin of the American Society for
  Information Science & Technology Special Issue on Visual Search (http:/ / uwf. edu/ ruzwyshyn/ 2009PDF/
  Bulletin_JunJul09_Finaloptimized. pdf). June/July 2009. 35:5 ISSN: 1550-8366.


• alipr.com (http:/ / http://www. alipr. com) Automatic image tagging and visual image search. Developed with Stanford
  and Penn State technologies.


• CIRES (http:/ / amazon. ece. utexas. edu/ ~qasim/ research. htm) Image retrieval system developed by the
  University of Texas at Austin.


• FIRE (http:/ / thomas. deselaers. de/ FIRE) Image retrieval system developed by the RWTH Aachen University,
  Aachen, Germany.


• GIFT (http:/ / http://www. gnu. org/ software/ gift/ ) GNU Image Finding Tool, originally developed at the University
  of Geneva, Switzerland.


• ImageCLEF (http:/ / http://www. imageclef. org) A benchmark to compare the performance of image retrieval systems.


• imgSeek (http:/ / http://www. imgseek. net) Open-source desktop photo collection manager and viewer with
  content-based search and many other features.


• isk-daemon (http:/ / server. imgseek. net) Open-source database server capable of adding content-based (visual)
  image searching to any image related website or software.


• img (Anaktisi) (http:/ / http://www. anaktisi. net) This Web-Solution implements a new family of CBIR descriptors.
  These descriptors combine in one histogram color and texture information and are suitable for accurately
  retrieving images.


• Caliph & Emir (http:/ / http://www. semanticmetadata. net/ ): Creation and Retrieval of images based on MPEG-7
  (GPL).


• img (Rummager) (http:/ / http://www. img-rummager. com): Image retrieval Engine (Freeware Application).


• PicsLikeThat (http:/ / http://www. picslikethat. com): Visual and semantic image retrieval.