Abstract
With the growing amount of multimedial content over the internet and broadcast systems, mechanisms for efficient information organization, manipulation and transmission are becoming indispensable. Optimization of the multimedia search and retrieval processes is nowadays an important area of development due to the difficulty to browse, filter and manage that big amount of data. The adoption of the MPEG-7 standard has a significant importance to simplify the image retrieval process. However, performance issues are still relevant when the retrieval must be accomplished in real time. This work presents an innovative and efficient approach of a Content-Based Retrieval Process using metric spaces implemented in heterogeneous resources according to the demand of computational power. Several implementations were made and comparative results are shown evidencing the benefits of the proposed approach.
Similar content being viewed by others
References
Shih-Fu, C., Sikora, T., Purl, A.: Overview of the MPEG-7 standard. Circuits Syst. Video Technol. 11, 688–695 (2001)
Sezan, I., van Beek, P.: MPEG-7 standard and its expected role in development of new information appliances. Consumer Electronics, 2000. ICCE. 2000 Digest of Technical Papers, pp. 274–275 (2000)
Rui, Y., Huang, T.S., Chang, S.F.: Digital image/video library and MPEG-7: standardization and research issues. IEEE Int. Conf. Acoust. Speech. Signal Process. 6, 3785–3788 (1998)
Vinod, V.V., Lindsay, A.: MPEG-7: its impact on research, industry, and the consumer. In: Proceedings IEEE International Conference on Multimedia Computing and Systems, pp. 406–407. Florence (1999)
Manjunath, B.S., Salembier, Philippe, Sikora, Thomas: MPEG-4: a multimedia compression standard for interactive applications and services. ISBN 0471, 486787 (2002)
Sikora, T.: MPEG digital video-coding standards. Signal Process. Mag. 14, 82–100 (1997)
Sikora, T.: MPEG digital audio-and video-coding standards. Signal Process. Mag. 14, 58 (1997)
Schafer, R.: MPEG-7 multimedia content description interface. Electron. Commun. Eng. J. 10, 253–262 (1998)
Bleschke, M., Madonski, R., Rudnicki, R.: Image retrieval system based on combined MPEG-7 texture and colour descriptors. In: MIXDES-16th International Conference Mixed Design of Integrated Circuits & Systems, pp. 635–639. Lodz (2009)
Shao, H., Wu, Y., Cui, W., Zhang, J.: Image retrieval based on MPEG-7 dominant color descriptor. In: The 9th International Conference for Young Computer Scientists, pp. 753–757. Hunan (2008)
Quackenbush, S., Lindsay, A.: Overview of MPEG-7 audio. IEEE Trans. Circuits Syst. Video Technol. 11(6), 725–729 (2001)
Sikora, T.: The MPEG-7 color layout descriptor: a compact image feature description for high-speed image/video segment retrieval. Int. Conf. Image Process. 1, 674–677 (2001)
Cieplinski, L.: The MPEG-7 color descriptors, pp. 11–20. Springer-Verlag GmbH, New York (2001)
Chávez, E., Navarro, G., Baeza-Yates, R., Marroquín. J.: Searching in metric spaces. ACM Comput. Surv. 33(3), 273–321 (2001)
Sharm, M., Batra, A.: Analysis of distance measures in content based image retrieval. Global J. Comput. Sci. Technol. G Interdiscipl. 14(2), 10–16 (2014)
Malik, F., Baharudin, B.: Analysis of distance metrics in content-based image retrieval using statistical quantized histogram texture features in the DCT domain. J. King Saud Univ. Comput. Inf. Sci. 25(2), 207–218 (2013)
Brisaboa, N.R., Farina, A., Pedreira, O., Reyes, N.: Similarity search using sparse pivots for efficient multimedia information retrieval. In: Eighth IEEE International Symposium on Multimedia (ISM’06), pp. 881–888. San Diego, CA (2006)
Krishnamachari, S., Abdel-Mottaleb, M.: Hierarchical clustering algorithm for fast image retrieval. In: Proceedings SPIE 3656, Storage and Retrieval for Image and Video Databases VII, pp. 427–435 (1998)
Cai, Y.: Image retrieval using boosting algorithm. http://www.stat.ucla.edu/~yizheng.cai/report.pdf. Accessed 14 May 2018
Pilevar, A.H.: CBMIR: Content-based image retrieval algorithm for medical image databases. J. Med. Signals Sens. 1(1), 12–18 (2011)
Liang, C., Wu, C., Zhou, X., Cao, W., Wang, S., Wang, L.: An image semantic retrieval system design and realization. Proceedings of 2005 International conference on machine learning and cybernetics, vol. 9, pp. 5284–5289 (2005)
Zhou, X.S., Huang, T.S.: CBIR: from low-level features to high-level semantics. In: Proceedings SPIE 3974, Image and Video Communications and Processing, pp. 1–6 (2000)
Navarro, G., Reyes, N.: Fully dynamic spatial approximation trees. In: Symposium on String Processing and Information Retrieval, pp. 254–270 (2002)
Navarro, G., Reyes, N.: Dynamic spatial approximation trees for massive data. In: Second International Workshop on Similarity Search and Applications, pp. 81–88. Prague (2009)
Burstein, P., Smith, A.J.: Efficient search in file-sharing networks. International Conference on Parallel and Distributed Systems, pp. 1–9. Hsinchu (2007)
Gil-Costa, V., Marin, M., Reyes, N.: Parallel query processing on distributed clustering indexes. J. Discret. Algorithms 7(1), 3–17 (2009)
Papadopoulos, A., Manolopoulos, Y.: Distributed processing of similarity queries. J. Distrib. Parallel Databases 9(1), 1573–1578 (2001)
Batko, M., Novak, D., Falchi, F., Zezula, P.: Scalability comparison of peerto-peer similarity search structures. Future Gener. Comput. Syst. 24(8), 834–848 (2008)
Catalyurek, U.V., Boman, E.G., Devine, K.D., Bozdag, D., Heaphy, R.T., Riesen, L.A.: A repartitioning hypergraph model for dynamic load balancing. J. Parallel Distrib. Comput. 69(8), 711–724 (2009)
Marin, M., Gil-Costa, V., Uribe, R.: Hybrid index for metric space databases. In: Bubak, M., van Albada, G.D., Dongarra, J., Sloot, P.M.A. (eds.) Computational Science—ICCS 2008. Lecture Notes in Computer Science, vol 5101, pp. 327–336. Springer, Berlin, Heidelberg (2008)
Balasubramani, R., Kannan, V.: Efficient use of MPEG-7 color layout and edge histogram descriptors in CBIR systems. Global J. Comput. Sci. Technol. 5(5), 157–163 (2009)
Kim, J.-H., Lim, H.-Y., Kang, D.-S.: An implementation of the video retrieval system by video segmentation. In: 14th Asia-Pacific Conference on Communications, pp. 1–5. Tokyo (2008)
Sniatala, P., Kapela, R., Rudnicki, R., Rybarczyk, A.: Efficient hardware architectures of selected MPEG-7 color descriptors. In: 15th European Signal Processing Conference, pp. 1672–1675. Poznan (2007)
Pandey, J.G., Karmakar, A., Shekhar, C., Gurunarayanan, S.: An FPGA-based architecture for local similarity measure for image/video processing applications. In: 28th International Conference on VLSI Design (VLSID), pp. 339–344. Bangalore (2015)
Chikhi, R., Derrien, S., Noumsi, A., Quinton, P.: Combining flash memory and FPGAs to efficiently implement a massively parallel algorithm for content-based image retrieval. Reconfigurable computing: architectures, tools and applications, third international workshop proceedings, pp. 247–258 (2007)
Pedraza, C., Castillo, E., Castillo, J., Bosque, J.L., Martinez, J.I., Robles, O.D., Cano, J., Huerta, P.: Content-based image retrieval algorithm acceleration in a low-cost reconfigurable FPGA cluster. J. Syst. Architect. 56(11), 633640 (2010)
Liang, Chen, Wu, Chenlu, Zhou, Xuegong, Cao, Wei, Wang, Shengye, Wang, Lingli: An FPGA-cluster-accelerated Match engine for content-based image retrieval. International Conference on Field-Programmable Technology (FPT), pp. 422–425 (2013)
Bay, Herbert, Ess, Andreas, Tuytelaars, Tinne, Van Gool, Luc: Speeded-Up Robust Features (SURF). Comput. Vis. Image Underst. 110(3), 346–359 (2008)
https://docs.opencv.org/master/db/deb/tutorial_display_image.html. Accessed 14 May 2018
Bossard, L., Guillaumin, M., Van Gool, L.: Food-101—mining discriminative components with random forests. European conference on computer vision (2014). http://data.vision.ee.ethz.ch/cvl/food-101.tar.gz. Accessed June 2016
Acknowledgements
This research was supported by the Spanish Ministry of Economy and Competitiveness under the project REBECCA, (TEC2014-58036-C4-1-R) and by the Regional Government of Castilla-La Mancha under the project SAND, (PEII-2014-046-P)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Molina, R., Gazzano, J.D., Rincon, F. et al. Heterogeneous SoC-based acceleration of MPEG-7 compliance image retrieval process. J Real-Time Image Proc 15, 161–172 (2018). https://doi.org/10.1007/s11554-018-0788-6
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11554-018-0788-6