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Design and Development of an Image Classification and Recognition System for CubeSat Constellation

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International Journal of Computer Applications
© 2011 by IJCA Journal
Volume 36 - Number 11
Year of Publication: 2011
Authors:
Jean Marie Gashayija
Prof. Elmarie Biermann
10.5120/4534-6444

Jean Marie Gashayija and Prof. Elmarie Biermann. Article: Design and Development of an Image Classification and Recognition System for CubeSat Constellation. International Journal of Computer Applications 36(11):26-30, December 2011. Full text available. BibTeX

@article{key:article,
	author = {Jean Marie Gashayija and Prof. Elmarie Biermann},
	title = {Article: Design and Development of an Image Classification and Recognition System for CubeSat Constellation},
	journal = {International Journal of Computer Applications},
	year = {2011},
	volume = {36},
	number = {11},
	pages = {26-30},
	month = {December},
	note = {Full text available}
}

Abstract

The major problems with stored images in large image database are retrieval of precisely, clear images and semantic gap. Proposed methodology approach, author will arrange, classify and categorize image into database in order to solve identified problem of retrieval and semantic gap. This proposal in progress is to solve this underlying problem of semantic gap for large images databases for small satellite database (such as CubeSats constellation) and look as well effective efficiency algorithm to improve existing methods. This paper proposes a solution based on image classification and recognition methods (such k-nearest classification and support vector machine methods) to solve this underlying semantic gap problem.

References

  • Bach,R.J.,Fuller.C.,Gupta,A.,Hamparur,A.,Horowitza,B.,Jain,C.R.&Shu,C.R.1996. Virage image search: an open framework for image management. Proc SPIE, 2670:76-87.
  • Chang, C. Y., Wang, H.J & Li, C. F. 2009. Semantic analysis of real world images using support vector machine. Expert systems with application: An international journal, 36(7): 10560-10569.
  • Datta, R., Joshi, D., Jia, L. & Wang, J. 2008. Image retrieval: ideas Influences and trends of the new age. ACM computing surveys, 40(2):1-64, April.
  • French South Africa Institute of Technology.2011. http://www.cput.ac.za/fsati/. [10 August 2011].
  • Goodrum, A. & Spink, A.1999. Visual information seeking:A study of image queries on the World Wide Web.Proceedings of the 1999 annual Meeting of the American Society for Information Science.,October 31-Nov.4,1999,Washington,DC:665-674.
  • Goodrum, A. 2000. Image information retrieval: an overview of current research. Information Science Research, 3 (2):63-67.
  • Huiskes, J.M & Lew, S.M.2008. Performance evaluation of relevance feedback method.CIVR’08, ACM: 239-248.July 9.
  • Han, J.&Kamber,M.2006.Data mining:concepts and techniques.2nd ed.Hamilton:Morgan Kaufmann. March .
  • Idris, F. & Panchathan, S.1997.Review of image and video indexing techniques. Journal of visual Communication and image representation, 8(2):146-166, June.
  • Mishra, J., Sharma, A. & Chaturvedi, K. 2011 .An Unsupervised cluster based image retrieval algorithm using relevance feedback methods. International journal of managing information technology, 3(2):9-16, May.
  • Ray, A.K. & Acharya, T.2004.Information technology: principles and applications. New Delhi, Prentice hall.
  • Rui, Y., Huang, T.S. & Chang, S.F.1999. Image Retrieval: current techniques, promising directions and open issues. Journal of Visual Communication and Image Representation, 10(1):39-62.March 1.
  • Schor, D., Scowcroft, J., Nichols, C. & Kinsner, W.2009.A command and data handling unit for pico-satellite missions.Electrical and Computer Engineering, 2009.CCECE’09. IEEE Xplore Canadian Conference on, 3-6 May 2009. St.John, NL: 874-879.
  • Sivakumar M.V.K, Roy P.S., Harmsen K., Saha S.K.2004.Satellite remote sensing and GIS application in agricultural meteorology. Proceedings of the training workshop on,7-11 July,2003.Dehra Dun:1-23.
  • Smith, J.R, and Chang, S.F.1996. Local color and texture extraction and spatial query. IEEE International conference on image processing, 3:1011-1014.
  • Stricker, M. &Orengo, M.1995.Similirity of color images, in Storage and Retrieval for image and video Database III, Proc SPIE 2420:381-392.
  • Wang, Z.J.2001.Integrated region-based retrieval.Massachusetts.Kluwer academic publishers group.
  • Yang, C.2004.Content based image retrieval: a comparison between query by example and image browsing map approach. Journal of information science, 30(3):254-267.January 7.
  • Zhang, H. & Zhong, D.1995.A scheme for visual feature based image indexing.Proc.SPIE, 2420:36-46.