This paper attempts to discuss the evolution of the
retrieval techniques focusing on development, challenges and trends
of the image retrieval. It highlights both the already addressed and
outstanding issues. The explosive growth of image data leads to the
need of research and development of Image Retrieval. However,
Image retrieval researches are moving from keyword, to low level
features and to semantic features. Drive towards semantic features is
due to the problem of the keywords which can be very subjective and
time consuming while low level features cannot always describe high
level concepts in the users- mind.
[1] A. Rosenfeld. Picture processing by computer. ACM Computing
Surveys, 1(3):147{176, 1969.
[2] H. Tamura and S. Mori. A data management system for manipulating
large images. In Proceedings of Workshop on Picture Data Description
and Management, pages 45{54, Chicago, Illinois, USA, April 1977
[3] Yong Rui and Thomas S. Huang (1999) Image Retrieval: Current
Techniques, Promising Directions, and Open Issues. Journal of Visual
Communication and Image Representation 10, 39-62 (1999)
[4] R. Datta, D. Joshi, J. Li, and J. Z. Wang. Image retrieval: Ideas,
inuences, and trends of the new age. In ACM Computing Surveys,
2008Letter Symbols for Quantities, ANSI Standard Y10.5-1968.
[5] M. Worring and G. Schreiber. Semantic image and video indexing in
broad domains. IEEE Transactions on Multimedia, 9(5):909{911,
August 2007
[6] Shneiderman B and Kang H (2000) Direct Annotation: A Drag-and-
Drop Strategy for Labeling Photos. In: Proc. International Conference
Information Visualisation (IV2000). London, England.
[1] A. Rosenfeld. Picture processing by computer. ACM Computing
Surveys, 1(3):147{176, 1969.
[2] H. Tamura and S. Mori. A data management system for manipulating
large images. In Proceedings of Workshop on Picture Data Description
and Management, pages 45{54, Chicago, Illinois, USA, April 1977
[3] Yong Rui and Thomas S. Huang (1999) Image Retrieval: Current
Techniques, Promising Directions, and Open Issues. Journal of Visual
Communication and Image Representation 10, 39-62 (1999)
[4] R. Datta, D. Joshi, J. Li, and J. Z. Wang. Image retrieval: Ideas,
inuences, and trends of the new age. In ACM Computing Surveys,
2008Letter Symbols for Quantities, ANSI Standard Y10.5-1968.
[5] M. Worring and G. Schreiber. Semantic image and video indexing in
broad domains. IEEE Transactions on Multimedia, 9(5):909{911,
August 2007
[6] Shneiderman B and Kang H (2000) Direct Annotation: A Drag-and-
Drop Strategy for Labeling Photos. In: Proc. International Conference
Information Visualisation (IV2000). London, England.
@article{"International Journal of Information, Control and Computer Sciences:55375", author = "Hui Hui Wang and Dzulkifli Mohamad and N.A Ismail", title = "Image Retrieval: Techniques, Challenge, and Trend", abstract = "This paper attempts to discuss the evolution of the
retrieval techniques focusing on development, challenges and trends
of the image retrieval. It highlights both the already addressed and
outstanding issues. The explosive growth of image data leads to the
need of research and development of Image Retrieval. However,
Image retrieval researches are moving from keyword, to low level
features and to semantic features. Drive towards semantic features is
due to the problem of the keywords which can be very subjective and
time consuming while low level features cannot always describe high
level concepts in the users- mind.", keywords = "content based image retrieval, keyword based imageretrieval, semantic gap, semantic image retrieval.", volume = "3", number = "12", pages = "2807-3", }