VisualSEEk: a fully automated content-based image query system. We describe a highly functional prototype system for searching by visual features in an image database. The VisualSEEk system is novel in that the user forms the queries by diagramming spatial arrangements of color regions. The system finds the images that contain the most similar arrangements of similar regions. Prior to the queries, the system automatically extracts and indexes salient color regions from the images. By utilizing efficient indexing techniques for color information, region sizes and absolute and relative spatial locations, a wide variety of complex joint color/spatial queries may be computed.

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  1. Krishnamoorthy, R.; Kalpana, J.: Fast retrieval of color objects with multidimensional orthogonal polynomials (2014) ioport
  2. Zhuang, Yi; Jiang, Nan; Wu, Zhiang; Li, Qing; Chiu, Dickson K. W.; Hu, Hua: Efficient and robust large medical image retrieval in mobile cloud computing environment (2014) ioport
  3. Iqbal, Kashif; Odetayo, Michael O.; James, Anne: Content-based image retrieval approach for biometric security using colour, texture and shape features controlled by fuzzy heuristics (2012) ioport
  4. Yu, Zhiwen; Wong, Hau-San; You, Jane; Han, Guoqiang: Visual query processing for efficient image retrieval using a SOM-based filter-refinement scheme (2012) ioport
  5. Abdullah, Azizi; Veltkamp, Remco C.; Wiering, Marco A.: Fixed partitioning and salient points with MPEG-7 cluster correlograms for image categorization (2010)
  6. Bartolini, Ilaria; Ciaccia, Paolo; Patella, Marco: Query processing issues in region-based image databases (2010) ioport
  7. Gondra, Iker; Xu, Tao: Image region re-weighting via multiple instance learning (2010)
  8. Huang, Wei; Gao, Yan; Chan, Kap Luk: A review of region-based image retrieval (2010) ioport
  9. Liu, Guang-Hai; Zhang, Lei; Hou, Ying-Kun; Li, Zuo-Yong; Yang, Jing-Yu: Image retrieval based on multi-texton histogram (2010)
  10. Yap, Kim-Hui; Wu, Kui; Zhu, Ce: Knowledge propagation in collaborative tagging for image retrieval (2010) ioport
  11. Yu, Zhiwen; Zhou, Xingshe; Zhou, Liang; Du, Kejun: A hybrid similarity measure of contents for TV personalization (2010) ioport
  12. Zhang, Shile; Li, Bin; Xue, Xiangyang: Semi-automatic dynamic auxiliary-tag-aided image annotation (2010)
  13. Banerjee, Minakshi; Kundu, Malay K.; Maji, Pradipta: Content-based image retrieval using visually significant point features (2009) ioport
  14. Bhargava, Medha; Chen, Chia-Chih; Ryoo, M. S.; Aggarwal, J. K.: Detection of object abandonment using temporal logic (2009) ioport
  15. Ren, W.; Singh, S.; Singh, M.; Zhu, Y. S.: State-of-the-art on spatio-temporal information-based video retrieval (2009)
  16. Vassilieva, N. S.: Content-based image retrieval methods (2009) ioport
  17. Deselaers, Thomas; Keysers, Daniel; Ney, Hermann: Features for image retrieval: An experimental comparison (2008) ioport
  18. Guldogan, Esin; Gabbouj, Moncef: Feature selection for content-based image retrieval (2008)
  19. Heesch, Daniel: A survey of browsing models for content based image retrieval (2008) ioport
  20. Kim, Woo-Cheol; Song, Ji-Young; Kim, Seung-Woo; Park, Sanghyun: Image retrieval model based on weighted visual features determined by relevance feedback (2008) ioport

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