Concept-based image indexing, also variably named as "description-based" or "text-based" image indexing/retrieval, refers to retrieval from text-based indexing of images that may employ keywords,
subject headings, captions, or natural language text (Chen & Rasmussen, 1999). It is opposed to Content-based image retrieval. Indexing is a technique used in CBIR.
Chu (2001) confirms that there exist two distinctive research groups employing the content-based and description-based approaches, respectively. However, research in the content-based domain is currently dominating in the field, while the other approach has less visibility.
Ahmad, K., M. Tariq, B. Vrusias and C.Handy. 2003. Corpus-based thesaurus construction for image retrieval in specialist domains. In Sebastiani, F. (ed.). Proceedings of the 25th European Conference on Information Retrieval Research (ECIR-03). 502–510. Heidelberg: Springer Verlag.
Angeles, M. (1998). Information Organization and Information Use of Visual Resources Collections. VRA Bulletin, 25 (3), 51-58.
[1]
Chu, H. T. (2001). Research in image indexing and retrieval as reflected in the literature. Journal of the American Society for Information Science and Technology, 52(12), 1011-1018.
Fidel, R.; Hahn, T. B.; Rasmussen, E. M. & Smith, P. J. (1994). Challenges in Indexing Electronic Text and Images. Medford, NJ: Learned Information. (ASIS Monograph Series)
Heidorn, P. B. & Sandore, B. (Eds.). (1997). Digital Image Access & Retrieval: Proceedings of the 1996 Clinic on Library Applications of Data Processing. Illinois: University of Illinois, Graduate School of Library and Information Science.
Jörgensen, C. (2003). Image Retrieval. Theory and Research. Lanham, Maryland: Scarecrow Press.
Lamy-Rousseau, F. (1984). Classification des images, materiels et donnees = Classification of images, materials and data . 2nd ed. Longueuil, Quebec: F. Lamy-Rousseau.
Panofsky, E. (1962). Studies in Icology: Humanistic themes in the art of the Renaissance. New York: Harper & Row.
Rasmussen, E. M. (1997). Indexing images. Annual Review of Information Science and Technology, 32, 169-196.
Shatford, S. (1986). Analyzing the Subject of a Picture: A Theoretical Approach. Cataloging and Classification Quarterly, 6(3), 39-62.
Wang, Xin; Erdelez, Sanda; Allen, Carla; Anderson, Blake; Cao, Hongfei & Shyu, Chi-Ren (2011). Role of Domain Knowledge in Developing User-Centered Medical-Image Indexing. Journal of the American Society for Information Science and Technology, early view October 2011.
doi:
10.1002/asi.21686
Ørnager, S. (1997). Image retrieval - Theoretical analysis and empirical user studies on accessing information in images. Proceedings of the ASIS annual meeting, 34, 202-211.
Concept-based image indexing, also variably named as "description-based" or "text-based" image indexing/retrieval, refers to retrieval from text-based indexing of images that may employ keywords,
subject headings, captions, or natural language text (Chen & Rasmussen, 1999). It is opposed to Content-based image retrieval. Indexing is a technique used in CBIR.
Chu (2001) confirms that there exist two distinctive research groups employing the content-based and description-based approaches, respectively. However, research in the content-based domain is currently dominating in the field, while the other approach has less visibility.
Ahmad, K., M. Tariq, B. Vrusias and C.Handy. 2003. Corpus-based thesaurus construction for image retrieval in specialist domains. In Sebastiani, F. (ed.). Proceedings of the 25th European Conference on Information Retrieval Research (ECIR-03). 502–510. Heidelberg: Springer Verlag.
Angeles, M. (1998). Information Organization and Information Use of Visual Resources Collections. VRA Bulletin, 25 (3), 51-58.
[1]
Chu, H. T. (2001). Research in image indexing and retrieval as reflected in the literature. Journal of the American Society for Information Science and Technology, 52(12), 1011-1018.
Fidel, R.; Hahn, T. B.; Rasmussen, E. M. & Smith, P. J. (1994). Challenges in Indexing Electronic Text and Images. Medford, NJ: Learned Information. (ASIS Monograph Series)
Heidorn, P. B. & Sandore, B. (Eds.). (1997). Digital Image Access & Retrieval: Proceedings of the 1996 Clinic on Library Applications of Data Processing. Illinois: University of Illinois, Graduate School of Library and Information Science.
Jörgensen, C. (2003). Image Retrieval. Theory and Research. Lanham, Maryland: Scarecrow Press.
Lamy-Rousseau, F. (1984). Classification des images, materiels et donnees = Classification of images, materials and data . 2nd ed. Longueuil, Quebec: F. Lamy-Rousseau.
Panofsky, E. (1962). Studies in Icology: Humanistic themes in the art of the Renaissance. New York: Harper & Row.
Rasmussen, E. M. (1997). Indexing images. Annual Review of Information Science and Technology, 32, 169-196.
Shatford, S. (1986). Analyzing the Subject of a Picture: A Theoretical Approach. Cataloging and Classification Quarterly, 6(3), 39-62.
Wang, Xin; Erdelez, Sanda; Allen, Carla; Anderson, Blake; Cao, Hongfei & Shyu, Chi-Ren (2011). Role of Domain Knowledge in Developing User-Centered Medical-Image Indexing. Journal of the American Society for Information Science and Technology, early view October 2011.
doi:
10.1002/asi.21686
Ørnager, S. (1997). Image retrieval - Theoretical analysis and empirical user studies on accessing information in images. Proceedings of the ASIS annual meeting, 34, 202-211.