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Application of the fuzzy logic in content-based image retrieval
Keywords:
Content-based Image Retrieval, Fuzzy Inference, Weight Assignment, Subjectivity of Human PerceptionsAbstract
This paper imports the fuzzy logic into image retrieval to deal with the vagueness and ambiguity of human judgment of image similarity. Our retrieval system has the following properties: firstly adopting the fuzzy language variables to describe the similarity degree of image features, not the features themselves; secondly making use of the fuzzy inference to instruct the weights assignment among various image features; thirdly expressing the subjectivity of human perceptions by fuzzy rules impliedly; lastly we propose an improvement on the traditional histogram called the Average Area Histogram (AAH) to represent color features. Experimentally we realized a fuzzy logic-based image retrieval system with good retrieval performance.
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References
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[2] Rui Y,Huang TS, “Mehrotra S. Content-based Image Retrieval With Relevance Feedback in MARS”, ICIP,1997, pp. 815-818
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[4] Chih-Yi Chiu, Hsin-Chin Lin, Shi-Nine Yang, “A Fuzzy Logic CBIR System”, The 12th IEEE International Conference on Fuzzy Systems, 2003, pp.1171-1176
[5] J. K. Wu, Y. H. Ang, P. C. Lam, S. K. Moorthy, A. D. Narasimhalu, “Facial image retrieval, identification, and inference system”, The first ACM international conference on Multimedia, California, United States, 1993, pp. 47-55
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[7] Mostafa, T., Abbas, H. M., Wahdan A. A, “On the Use of Hierarchical Color Moments for Image Indexing and Retrieval”, IEEE International Conference on Systems, Man and Cybernetics, Hammamet, Tunisia, 2000, pp.6
[8] Swain, M J and Ballard, D.H., “Color indexing”, International Journal of Computer Vision, 1991, Vol.7, No.1, pp. 11-32
[9] Mlsna, P.A, Rodriguez, J.J, “Efficient indexing of multi-color sets for content-based image retrieval”, The 4th IEEE Southwest Symposium on Image Analysis and Interpretation, Texas, USA, 2000, pp.116.
[10] Androutsos, D., Plataniotiss, K.N. Venetsanopoulos, N., “Distance measures for color image retrieval”, ICIP, Chicago, USA, 1998, pp. 770-774
[11] Pass, G. and Zabih, R, Histogram refinement for content-based image retrieval. WACV '96, Proceedings, Sarasoto, FL, 1996, pp. 96-102
[12] Colombo, C., Del Bimbo, A. and Genovesi, I., “Interactive image retrieval by color distributions”, IEEE International Conference on Multimedia Computing and Systems, Texas, USA, 1998, pp. 255-258
[13] Cinque, L., Levialdi, S., Olsen, K.A., Pellicano, A., “Color-based image retrieval using spatial-chromatic histograms”, IEEE International Conference on Multimedia computing and Systems, Florence, Italy, 1999, pp.969-973
[14] Rickman, Richard M., Stonham, T.jhon, “Content-based image retrieval using color tuple histograms”, Proceedings of the SPIE-The International Society for Optical Engineering, 1996, Vol.2670, pp. 2-7
[15] Hsu, wynne, Chua, T.S., Pung, H.K., “Integrated color-spatial approach to content-based image retrieval”, Proceedings of the ACM International Multimedia Conference & Exhibition, 1995, pp. 305-313
[16] Safar, M. Shahabi, C. and Sun, X., “Image retrieval by shape: a comparative study”, International Conference on Multimedia and Expo, New York, USA, 2000, pp.141-144
[17] Ezer, N.; Anarim, E., Sankur, B.A., “Comparative study of moment invariants and Fourier descriptors in planar shape recognition”, 7th Mediterranean Electro technical
Conference, Turkey, 1994, 242-245
[18] Jiawei Han, Micheline Kamber, Data Mining Conception And Technology, Beijing: Mechanism industry, China, 2001
[2] Rui Y,Huang TS, “Mehrotra S. Content-based Image Retrieval With Relevance Feedback in MARS”, ICIP,1997, pp. 815-818
[3] Kulkami, S., Verma, B., “Fuzzy Logic Based Texture Queries for CBIR”, Fifth International Conference on Computational Intelligence and Multimedia Applications, 2003, pp.223-228
[4] Chih-Yi Chiu, Hsin-Chin Lin, Shi-Nine Yang, “A Fuzzy Logic CBIR System”, The 12th IEEE International Conference on Fuzzy Systems, 2003, pp.1171-1176
[5] J. K. Wu, Y. H. Ang, P. C. Lam, S. K. Moorthy, A. D. Narasimhalu, “Facial image retrieval, identification, and inference system”, The first ACM international conference on Multimedia, California, United States, 1993, pp. 47-55
[6] Banerjee, M., Kundu, M.K, “Content Based Image Retrieval With Fuzzy Geometrical Features”, The 12th IEEE International Conference on Fuzzy Systems, 2003, pp. 932-937
[7] Mostafa, T., Abbas, H. M., Wahdan A. A, “On the Use of Hierarchical Color Moments for Image Indexing and Retrieval”, IEEE International Conference on Systems, Man and Cybernetics, Hammamet, Tunisia, 2000, pp.6
[8] Swain, M J and Ballard, D.H., “Color indexing”, International Journal of Computer Vision, 1991, Vol.7, No.1, pp. 11-32
[9] Mlsna, P.A, Rodriguez, J.J, “Efficient indexing of multi-color sets for content-based image retrieval”, The 4th IEEE Southwest Symposium on Image Analysis and Interpretation, Texas, USA, 2000, pp.116.
[10] Androutsos, D., Plataniotiss, K.N. Venetsanopoulos, N., “Distance measures for color image retrieval”, ICIP, Chicago, USA, 1998, pp. 770-774
[11] Pass, G. and Zabih, R, Histogram refinement for content-based image retrieval. WACV '96, Proceedings, Sarasoto, FL, 1996, pp. 96-102
[12] Colombo, C., Del Bimbo, A. and Genovesi, I., “Interactive image retrieval by color distributions”, IEEE International Conference on Multimedia Computing and Systems, Texas, USA, 1998, pp. 255-258
[13] Cinque, L., Levialdi, S., Olsen, K.A., Pellicano, A., “Color-based image retrieval using spatial-chromatic histograms”, IEEE International Conference on Multimedia computing and Systems, Florence, Italy, 1999, pp.969-973
[14] Rickman, Richard M., Stonham, T.jhon, “Content-based image retrieval using color tuple histograms”, Proceedings of the SPIE-The International Society for Optical Engineering, 1996, Vol.2670, pp. 2-7
[15] Hsu, wynne, Chua, T.S., Pung, H.K., “Integrated color-spatial approach to content-based image retrieval”, Proceedings of the ACM International Multimedia Conference & Exhibition, 1995, pp. 305-313
[16] Safar, M. Shahabi, C. and Sun, X., “Image retrieval by shape: a comparative study”, International Conference on Multimedia and Expo, New York, USA, 2000, pp.141-144
[17] Ezer, N.; Anarim, E., Sankur, B.A., “Comparative study of moment invariants and Fourier descriptors in planar shape recognition”, 7th Mediterranean Electro technical
Conference, Turkey, 1994, 242-245
[18] Jiawei Han, Micheline Kamber, Data Mining Conception And Technology, Beijing: Mechanism industry, China, 2001
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Published
2005-04-01
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[1]
“Application of the fuzzy logic in content-based image retrieval”, JCS&T, vol. 5, no. 01, pp. p. 19–24, Apr. 2005, Accessed: Jan. 14, 2026. [Online]. Available: https://journal.info.unlp.edu.ar/JCST/article/view/883
