Image Retrieval Based on Multi-Feature Fusion for Heterogeneous Image Databases
Selecting an appropriate image representation is the most important factor in implementing an effective Content-Based Image Retrieval (CBIR) system. This paper presents a multi-feature fusion approach for efficient CBIR, based on the distance distribution of features and relative feature weights at the time of query processing. It is a simple yet effective approach, which is free from the effect of features' dimensions, ranges, internal feature normalization and the distance measure. This approach can easily be adopted in any feature combination to improve retrieval quality. The proposed approach is empirically evaluated using two benchmark datasets for image classification (a subset of the Corel dataset and Oliva and Torralba) and compared with existing approaches. The performance of the proposed approach is confirmed with the significantly improved performance in comparison with the independently evaluated baseline of the previously proposed feature fusion approaches.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1126904Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 986
 P. S. Hiremath, J. Pujari, "Content based image retrieval based on colour, texture and shape features" In 15th International Conference on Advance Computing and Communications, 2007 pp. 780-784.
 S. A. Chatzichristoﬁs, A. Arampatzis, "Late fusion of compact composite descriptors for retrieval from heterogeneous image databases", In 33rd International Conference on Special Interest Group on Information Retrieval SIGIR, 2010, pp.825-826.
 X. Yuan, J. Yu, Z. Qin, T. Wan, "A SIFT-LBP image retrieval model based on bag-of-features". In Proc. IEEE ICIP 18th International Conference on Image Processing, 2011, pp. 1061-1064.
 M. H. Saad, H. I. Saleh, H. Konbor, M. Ashour, "Image retrieval based on integration between YCbCr colour histogram and shape feature", In Proc. ICENCO 7th International Computer Engineering Conference, 2012, pp. 97-102.
 N. S. Mansoori, M. Nejati, P. Razzaghi, S. Samavi, "Bag of visual words approach for image retrieval using colour information", In Proc. ICEE 21st Iranian Conference on Electrical Engineering, 2013, pp. 1-6.
 A. Arampatzis, J. Kamps, "A signal-to-noise approach to score normalization", In ACM International Conference on Information and Knowledge Management CIKM, 2009, pp797–806.
 G. Qiu, "Indexing chromatic and achromatic patterns for content-based", Journal of pattern recognition, B2002, pp. 1675-1686.
 M.H. Rahmana, M.R. Pickering, M.R. Frater, "Scale and Rotation Invariant Gabor Features for Texture Retrieval", In Proc. DICTA International Conference on Digital Image Computing Techniques and Applications, 2011, pp. 602-607.
 S. Agarwal, A.K. Verma, P. Singh, "Content Based Image Retrieval using Discrete Wavelet Transform and Edge Histogram Descriptor", In Proc. ISCON International Conference on Information Systems and Computer Networks, 2013, pp. 19-23.
 V. Takala, T. Ahoen, M. Pietikainen, "Block-based methods for image retrieval using local binary patterns", In Proc. of the 14th Scandinavian Conference on Image Analysis, 2005, pp. 882-891.
 J. A. Aslam , M. Montague. "Models for Metasearch" , Proceedings of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2001, pp. 276–284.
 M. Jovic, Y. Hatakeyama, Yutaka, F. Dong, K. Hirota, " Image Retrieval Based on Similarity Score Fusion from Feature Similarity Ranking Lists ", Fuzzy Systems and Knowledge Discovery, 2006, pp. 461-470
 Y. Minaqiang, K. Kidiyo, R. Joseph, "A survey of shape feature extraction techniques", Journal of Pattern Recognition, 2008, pp. 43-90.
 R. Manthalkar, P. K. Biswas, B. N. Chatterji, "Rotation Scale invariant Texture Features Using Discrete Wavelet Packet Transform", Journal of Pattern Recognition, 2003, pp. 2455-2462.
 J. Li, J. W. Wang, "Automatic linguistic indexing of pictures by a statistical modeling approach", IEEE transaction on Pattern Analysis and Machine Intelligence, vol. 25(9), 2003, pp. 1075-1087.
 A. Oliva, A. Torralba, "Modeling the shape of the scene: A Holistic representation of the spatial envelope, International Journal of Computer Vision, vol. 42(3), 2001, pp. 145-175.