Recuperação de Imagens: Desafios e Novos Rumos
Resumo
Atualmente, um grande conjunto de imagens digitais vem sendo gerado, manipulado e armazenado em bancos de imagens. Dado o tamanho desses acervos, prover meios de recuperar imagens de forma eficiente e eficaz é essencial. Esse é o objetivo dos Sistemas de Recuperação de Imagens por Conteúdo. Tradicionalmente, tais sistemas são baseados em critérios objetivos de baixo nível para representar e comparar imagens. Porém, usuários destes sistemas tendem a utilizar elementos subjetivos para comparar imagens. Considerar esses elementos tem proporcionado uma melhora, em termos de eficácia, no processo de recuperação de imagens. Este artigo discute propostas relacionadas à incorporação de informação semântica à recuperação de imagens por conteúdo, destacando novos desafios desse campo.Referências
Almeida, J., Rocha, A., Torres, R., and Goldestein, S. (2008). Making Colors Worth more than a Thousand Words. In The 23th Annual ACM Symposium on Applied Computing, pages 1184–1190, Fortaleza.
Antani, A., Kasturi, R., and Jain, R. (2002). A Survey on the Use of Pattern Recognition Methods for Abstraction, Indexing and Retrieval of Images and Video. Pattern Recognition, 35(4):945–965.
Bugatti, P. H., Traina, A. J. M., and C. Traina, J. (2008). Assessing the best integration between distance-function and image-feature to answer similarity queries. In Proceedings of the ACM symposium on Applied computing, pages 1225–1230.
Carvalho, A. C. P. L. F., Brayner, A., Loureiro, A., Furtado, A. L., v. Staa, A., Lucena, C. J. P., S., C. S., Medeiros, C. M. B., Lucchesi, C. L., Silva, E. S., Wagner, F. R., Simon, I., Wainer, J., Maldonado, J. C., Oliveira, J. P. M., Ribeiro, L., Velho, L., calves, M. A. G., Baranauskas, M. C. C., Mattoso, M., Ziviani, N., Navaux, P. O. A., da S. Torres, R., Almeida, V. A. F., Jr., W. M., and Kohayakawa, Y. (2006). Grandes Desafios da Pesquisa em Computação no Brasil – 2006 - 2016. In Seminário Grandes Desafios da Sociedade Brasileira de Computação, São Paulo, SP, Brasil.
Chang, J.-W. and Kim, Y.-J. (2001). Spatial-match iconic image retrieval with ranking in multimedia databases. In WAIM ’01: Proceedings of the Second International Conference on Advances in Web-Age Information Management, pages 3–13, London, UK.
Chang, S. K., Shi, Q. Y., and Yan, C. W. (1987). Iconic indexing by 2-d strings. IEEE Trans. Pattern Anal. Mach. Intell., 9(3):413–428.
Ciaccia, P., Patella, M., and Zezula, P. (1997). M-tree: An Efficient Access Method for Similarity Search in Metric Spaces. In Proceedings of 23rd International Conference on Very Large Data Bases, pages 426–435, Athens, Greece.
Câmara, G., Casanova, M., Hemerly, A., Magalhães, G., and Medeiros, C. (1997). Anatomia de Sistemas de Informação Geográfica. Sagres Editora, Curitiba-PR, Brasil.
Datta, R., Joshi, D., Li, J., and Wang, J. Z. (2008). Image retrieval: Ideas, influences, and trends of the new age. ACM Computing Surveys, 40(2).
del Val Cura, L. M. (2002). Um modelo para recuperação por conteudo de imagens de sensoriamento remoto. PhD thesis, Universidade Estadual de Campinas. Instituto de Computação, Campinas, SP.
Gonzalez, R. C. and Woods, R. E. (2001). Digital image processing. Electrical and Computer Engineering Series. Addison-Wesley Longman Publishing Co. Inc., 2nd edition.
Kherfi, M. L., Ziou, D., and Bernardi, A. (2004). Image retrieval from the world wide web: Issues, techniques, and systems. ACM Comput. Surv., 36(1):35–67.
Kim, D.-H., Chung, C.-W., and Barnard, K. (2005). Relevance feedback using adaptive clustering for image similarity retrieval. Journal of Systems and Software, 78(1):9–23.
Lin, W.-H., Jin, R., and Hauptmann, A. (2003). Web image retrieval re-ranking with relevance model. In International Conference on Web Intelligence, page 242.
Liu, Y., Zhang, D., Lu, G., and Ma, W.-Y. (2007). A survey of content-based image retrieval with high-level semantics. Pattern Recognition, 40(1):262–282.
Penatti, O. B. and Torres, R. (2007). Descritor de Relacionamento Espacial baseado em Partições. In XXVI Concurso de Trabalhos de Iniciação Científica, XXVII Congresso da Sociedade Brasileira de Computação, Rio de Janeiro, Brazil.
Rui, Y., Huang, T. S., Ortega, M., and Mehrotra, S. (1998). Relevance Feedback: A Power Tool for Interactive Content-Based Image Retrieval. IEEE Transactions on Circuits and Systems for Video Technology, 8(5):644–655.
Sebastian, T. B., Klein, P. N., and Kimia, B. B. (2002). Shock-based indexing into large shape databases. In ECCV, pages 731–746.
Smeulders, A. W. M., Worring, M., Santini, S., Gupta, A., and Jain, R. (2000). Content-based image retrieval at the end of the early years. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(12):1349–1380.
Swain, M. and Ballard, D. (1991). Color Indexing. International Journal of Computer Vision, 7(1):11–32.
Tamura, H., Mori, S., and Yamawaki, T. (1978). Texture features corresponding to visual perception. IEEE Transactions on Systems, Man and Cybernetics, 8(6):460–473.
Torres, R. and Falcão, A. X. (2006). Content-Based Image Retrieval: Theory and Applications. Revista de Informática Teórica e Aplicada, 13(2):161–185.
Xu, Z., Xu, X., Yu, K., and Tresp, V. (2003). A Hybrid Relevance-Feedback Approach to Text Retrieval. Proceedings of the 25th European Conference on Information Retrieval Research, Lecture Notes in Computer Science, 2633:81–293.
Yan, R. and Hauptmann, A. G. (2007). A review of text and image retrieval approaches for broadcast news video. Information Retrieval, 10(4-5):445–484.
Zhang, D. and Lu, G. (2004). Review of Shape Representation and Description. Pattern Recognition, 37(1):1–19.
Zhou, X. S. and Huang, T. S. (2003). Relevance feedback in image retrieval: A comprehensive review. Multimedia Systems, 8(6):536–544.
Antani, A., Kasturi, R., and Jain, R. (2002). A Survey on the Use of Pattern Recognition Methods for Abstraction, Indexing and Retrieval of Images and Video. Pattern Recognition, 35(4):945–965.
Bugatti, P. H., Traina, A. J. M., and C. Traina, J. (2008). Assessing the best integration between distance-function and image-feature to answer similarity queries. In Proceedings of the ACM symposium on Applied computing, pages 1225–1230.
Carvalho, A. C. P. L. F., Brayner, A., Loureiro, A., Furtado, A. L., v. Staa, A., Lucena, C. J. P., S., C. S., Medeiros, C. M. B., Lucchesi, C. L., Silva, E. S., Wagner, F. R., Simon, I., Wainer, J., Maldonado, J. C., Oliveira, J. P. M., Ribeiro, L., Velho, L., calves, M. A. G., Baranauskas, M. C. C., Mattoso, M., Ziviani, N., Navaux, P. O. A., da S. Torres, R., Almeida, V. A. F., Jr., W. M., and Kohayakawa, Y. (2006). Grandes Desafios da Pesquisa em Computação no Brasil – 2006 - 2016. In Seminário Grandes Desafios da Sociedade Brasileira de Computação, São Paulo, SP, Brasil.
Chang, J.-W. and Kim, Y.-J. (2001). Spatial-match iconic image retrieval with ranking in multimedia databases. In WAIM ’01: Proceedings of the Second International Conference on Advances in Web-Age Information Management, pages 3–13, London, UK.
Chang, S. K., Shi, Q. Y., and Yan, C. W. (1987). Iconic indexing by 2-d strings. IEEE Trans. Pattern Anal. Mach. Intell., 9(3):413–428.
Ciaccia, P., Patella, M., and Zezula, P. (1997). M-tree: An Efficient Access Method for Similarity Search in Metric Spaces. In Proceedings of 23rd International Conference on Very Large Data Bases, pages 426–435, Athens, Greece.
Câmara, G., Casanova, M., Hemerly, A., Magalhães, G., and Medeiros, C. (1997). Anatomia de Sistemas de Informação Geográfica. Sagres Editora, Curitiba-PR, Brasil.
Datta, R., Joshi, D., Li, J., and Wang, J. Z. (2008). Image retrieval: Ideas, influences, and trends of the new age. ACM Computing Surveys, 40(2).
del Val Cura, L. M. (2002). Um modelo para recuperação por conteudo de imagens de sensoriamento remoto. PhD thesis, Universidade Estadual de Campinas. Instituto de Computação, Campinas, SP.
Gonzalez, R. C. and Woods, R. E. (2001). Digital image processing. Electrical and Computer Engineering Series. Addison-Wesley Longman Publishing Co. Inc., 2nd edition.
Kherfi, M. L., Ziou, D., and Bernardi, A. (2004). Image retrieval from the world wide web: Issues, techniques, and systems. ACM Comput. Surv., 36(1):35–67.
Kim, D.-H., Chung, C.-W., and Barnard, K. (2005). Relevance feedback using adaptive clustering for image similarity retrieval. Journal of Systems and Software, 78(1):9–23.
Lin, W.-H., Jin, R., and Hauptmann, A. (2003). Web image retrieval re-ranking with relevance model. In International Conference on Web Intelligence, page 242.
Liu, Y., Zhang, D., Lu, G., and Ma, W.-Y. (2007). A survey of content-based image retrieval with high-level semantics. Pattern Recognition, 40(1):262–282.
Penatti, O. B. and Torres, R. (2007). Descritor de Relacionamento Espacial baseado em Partições. In XXVI Concurso de Trabalhos de Iniciação Científica, XXVII Congresso da Sociedade Brasileira de Computação, Rio de Janeiro, Brazil.
Rui, Y., Huang, T. S., Ortega, M., and Mehrotra, S. (1998). Relevance Feedback: A Power Tool for Interactive Content-Based Image Retrieval. IEEE Transactions on Circuits and Systems for Video Technology, 8(5):644–655.
Sebastian, T. B., Klein, P. N., and Kimia, B. B. (2002). Shock-based indexing into large shape databases. In ECCV, pages 731–746.
Smeulders, A. W. M., Worring, M., Santini, S., Gupta, A., and Jain, R. (2000). Content-based image retrieval at the end of the early years. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(12):1349–1380.
Swain, M. and Ballard, D. (1991). Color Indexing. International Journal of Computer Vision, 7(1):11–32.
Tamura, H., Mori, S., and Yamawaki, T. (1978). Texture features corresponding to visual perception. IEEE Transactions on Systems, Man and Cybernetics, 8(6):460–473.
Torres, R. and Falcão, A. X. (2006). Content-Based Image Retrieval: Theory and Applications. Revista de Informática Teórica e Aplicada, 13(2):161–185.
Xu, Z., Xu, X., Yu, K., and Tresp, V. (2003). A Hybrid Relevance-Feedback Approach to Text Retrieval. Proceedings of the 25th European Conference on Information Retrieval Research, Lecture Notes in Computer Science, 2633:81–293.
Yan, R. and Hauptmann, A. G. (2007). A review of text and image retrieval approaches for broadcast news video. Information Retrieval, 10(4-5):445–484.
Zhang, D. and Lu, G. (2004). Review of Shape Representation and Description. Pattern Recognition, 37(1):1–19.
Zhou, X. S. and Huang, T. S. (2003). Relevance feedback in image retrieval: A comprehensive review. Multimedia Systems, 8(6):536–544.
Publicado
12/07/2008
Como Citar
TORRES, Ricardo da S.; ZEGARRA, Javier A. M.; SANTOS, Jefersson A. dos; FERREIRA, Cristiano D.; PENATTI, Otávio A. B.; ANDALÓ, Fernanda; ALMEIDA, Jurandy.
Recuperação de Imagens: Desafios e Novos Rumos. In: SEMINÁRIO INTEGRADO DE SOFTWARE E HARDWARE (SEMISH), 35. , 2008, Belém/PA.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2008
.
p. 223-237.
ISSN 2595-6205.
