A Comparison Study on Image Content Based Retrieval Systems

Year 2018, Volume: 9, 103 - 116, 28.12.2018

Saed Alqaraleh , Hersh Hama

Abstract

In recent years, multimedia searching has become an important research field. Multimedia files are one of the most important materials on the internet. Unfortunately, even for the state-of-the-art methods and applications based on accessing multimedia on the internet, it is hard to find the required files. The main purpose of this study is to investigate the performance of well-known image content-based retrieval techniques, i.e., Fuzzy Color and Texture Histogram (FCTH), Edge Histogram Descriptor (EHD), Scalable Color Descriptor (SCD), Color Layout Descriptor (CLD), Color and Edge Directivity Descriptor (CEDD), and Speed-Up Robust Feature (SURF) combined with Fast Library Approximate Nearest Neighbor (FLANN). In general, the objective of using these techniques is to find the query’s most relevant files and list them at the top of the retrieval list.

Several experiments have been conducted and it has been observed that FCTH and SCD outperform other studied techniques. On the other hand, for the SURF combined with FLANN approach, the results of most of the queries were below user expectations. In addition, extracting the feature vectors using this method requires a massive amount of memory. Overall, none of the studied CBIR descriptors can be used individually to build a full image retrieval system. In our opinion, multiple descriptors can be used simultaneously to achieve a more robust system and accurate results.

Keywords

content-based image retrieval techniques; re-ranking algorithm; implicit ranking; multimedia search engines; information retrieval

References

• Amanatiadis, A., Kaburlasos, V.G., Gasteratos, A., Papadakis, S.E., Evaluation of shape descriptors for shape-based image retrieval, Image Processing, IET, 5(5)(2011), 493–499.
• Balasubramani, R., Kannan, D.V., Ecient use of MPEG-7 color layout and edge histogram descriptors in CBIR systems, Global Journal of Computer Science and Technology, 9(4)(2009), 157–163.
• Bay, H., Ess, A., Tuytelaars, T., Van Gool, L., Speeded-up robust features (SURF), Computer vision and image understanding, 110(3)(2008), 346–359.
• Chatzichristofis, S.A., Boutalis, Y.S., FCTH: Fuzzy color and texture histogram-a low level feature for accurate image retrieval, In Image Analysis for Multimedia Interactive Services, 2008. WIAMIS’08. Ninth International Workshop on IEEE, (2008), 191–196.
• Duan, L., Li, W., Tsang, I.W.H., Xu, D., Improving web image search by bag-based reranking, Image Processing, IEEE Transactions on, 20(11)(2011), 3280–3290.
• Huiskes, M.J., Thomee, B., Lew, M.S., New trends and ideas in visual concept detection: the MIR flickr retrieval evaluation initiative, In Proceedings of the international conference on Multimedia information retrieval, ACM, (2010), 527–536.
• Jain, H., Lodha, R., Deulkar, K., Web-based Image Search using Image Re-Ranking Technique: A Review Paper, International Journal of Current Engineering and Technology, 4(5)(2014), 3300–3303.
• Jalab, H.A., Image retrieval system based on color layout descriptor and Gabor filters, In Open Systems (ICOS), 2011 IEEE Conference on IEEE, (2011), 32–36.
• Kekre, D.H., Thepade, S.D., Mukherjee, P., Wadhwa, S., Kakaiya, M., Singh, S., Image retrieval with shape features extracted using gradient operators and slope magnitude technique with BTC, International Journal of Computer Applications (IJCA), 6(8)(2010), 28–33.
• Khokher, A., Talwar, R., Content-based Image Retrieval: Feature Extraction Techniques and Applications, In Conference proceedings, Proceedings published in International Journal of Computer Applications (IJCA), (2012), 9–14.
• Kumar, P.P., Aparna, D.K., Rao, K.V., Compact Descriptors for Accurate Image Indexing And Retrieval: Fcth And Cedd, International Journal of Engineering Research and Technology (IJERT), 1(8)(2012).
• Li, J., Wang, J.Z., Automatic linguistic indexing of pictures by a statistical modeling approach, IEEE Transactions on pattern analysis and machine intelligence, 25(9)(2003), 1075–1088.
• Manjunath, B.S., Ohm, J.R., Vasudevan, V.V., Yamada, A., Color and texture descriptors, IEEE Transactions on circuits and systems for video technology, 11(6)(2001), 703–715.
• M.Tech, V., Jagadeesan, J., Isaac, A., Web Image Search Reranking Using CBIR, International Journal of Computer Science & Engineering Technology (IJCSET), 5(2014)(2229-3345), 348–360.
• Microsoft, Microsoft Research Cambridge Object Recognition Image Database, (2016) Retrieved from “https://www.microsoft.com/enus /download/details.aspx?id=52644”.
• Ordonez, V., Han, X., Kuznetsova, P., Kulkarni, G., Mitchell, M., Yamaguchi, K., Stratos, K., Goyal, A., Dodge, J., Mensch, A., Daum´e III, H., Large scale retrieval and generation of image descriptions, International Journal of Computer Vision, 119(1)(2015), 46–59.
• Pedronette, D.C.G., Torres, R.D.S., Image re-ranking and rank aggregation based on similarity of ranked lists, Pattern Recognition, 46(8)(2013), 2350–2360.
• Schaefer, G., Stich, M., UCID: An uncompressed color image database, In Storage and Retrieval Methods and Applications for Multimedia, 5307(2003), 472–481.
• Syed, H.S., Arif, I.U., Saeeda, N., Noor ul, A.Kh., Muhammad, I.R., AlHaqbani, B., Content-Based Image Retrieval Using Texture Color Shape and Region, International Journal of Advanced Computer Science and Applications (IJACSA), 7(1)(2016), 418–426.
• Wang, X., Liu, K., Tang, X., Query-specific visual semantic spaces for web image re-ranking, In Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference, (2011), 857–864.
• Wang, J.Z., Li, J., Wiederhold, G., SIMPLIcity: Semantics-sensitive integrated matching for picture libraries, IEEE Transactions on pattern analysis and machine intelligence, 23(9)(2001), 947–963.
• Wang, X., Qiu, S., Liu, K., Tang, X., Web Image Re-Ranking Using Query-Specific Semantic Signatures, IEEE Transactions on Pattern Analysis and Machine Intelligence, 36(4)(2014), 810–823.
• Won, C.S., Park, D.K., Park, S.J., Ecient use of MPEG-7 edge histogram descriptor, ETRI journal, 24(1)(2002), 23–30.
• Yang, L., Hanjalic, A., Prototype-based image search reranking, Multimedia, IEEE Transactions on, 14(3)(2012), 871–882.
• Yu, J., Rui, Y., Chen, B., Exploiting click constraints and multi-view features for image re-ranking, Multimedia, IEEE Transactions on, 16(1)(2014), 159–168.
• Zhang, D., Lu, G., Review of shape representation and description techniques, Pattern recognition, 37(1)(2004), 1-19.