A novel Virus Infection Clustering for Flower Images Identification

  • Authors:
  • Siu-Yeung Cho;Peh-Ti Lim

  • Affiliations:
  • Nanyang Technological University, Singapore;Nanyang Technological University, Singapore

  • Venue:
  • ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 02
  • Year:
  • 2006

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Abstract

Computer-aided flower identification is a very useful tool for plant species identification aspect. In this paper, a study was made on a development of content based image retrieval system to characterize flower images efficiently. In this system, a novel Virus Infection Clustering is proposed to cluster the image database to improve the searching efficiency. Experimental results show that the developed system can yield promising results for flower image retrieval.