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Effective Utilization of Image Information Using Data Mining Technique

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Recent Trends and Advances in Artificial Intelligence and Internet of Things

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 172))

Abstract

In recent, video databases data mining is widely used for various applications such as crime prevention, web searching, cultural heritage, advertising, news broadcasting, video, education and training and military. The advancement of databases specially the multimedia dates are in need to efficiently handle due to the growing amount of multimedia data include audio video, sound, animation, image etc. Revolution in the extensive database of computerized medias gives rise to the study of useful information from database. The study such as multimedia information retrieval, productive storage and organization of available information are in focus. This paper discuss how effectively handle the image data’s.

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References

  1. Regunathan, R., Xiong, Z., Divakaran, A., Ishikawa, Y.: Generation of sports highlights using a combination of supervised and unsupervised learning in the audio domain. In: ICICS-PCM Conference, Singapore (2003)

    Google Scholar 

  2. Divakaran, A., Peker, K.A., Radhakrishnan, R., Xiong, Z., Cabasson, R.: Video sumarization using MPEG-7 motion activity and audio features. In: Rosenfeld, A., DoDoermann, D., DeMenthon, D. (eds.) Video Mining. Kluwer Academic Publishers (2003)

    Google Scholar 

  3. Saravanan, D.: Video data image retrieval using—BRICH. World J. Eng. 14(4), 318–323 (2017)

    Google Scholar 

  4. Saravanan, D.: Image frame mining using indexing technique. In: Data Engineering and Intelligent Computing, Chapter 12, pp. 127–137. Springer Book series. ISBN:978-981-10-3223-3, July 2017

    Google Scholar 

  5. Xie, L., Chang, S-F., Divakaran, A., Sun, H.: Unsupervised mining of statistical temporal structures in video. In: Rosenfeld, A., Doermann, D., DeMenthon, D. (eds.) Video Mining. Kluwer Academic Publishers (2003)

    Google Scholar 

  6. Alemu, Y., Koh, J.B., Ikram, M., Kim, D-K.: Image retrieval in multimedia databases: a survey. In: Fifth International Conference on Intelligent Information Hiding and Multimedia Signal Processing (2009)

    Google Scholar 

  7. Hilbert, D.: Uber die stetige Abbildung einer Linie auf ein Flachenstuck. Math. Annalen, 38–40. [10] Bartolini, I., Ciacci, P., Waas, F.: Feedback bypass: a new approach to interactive similarity query processing. In: Proceeding of 27th Int’l Conference Very Large Data Base (VLDB’01), pp. 201–210 (2001)

    Google Scholar 

  8. Brunelli, R., Mich, O.: Image retrieval by examples. IEEE Trans. Multimed. 2(3), 164–171 (2000)

    Article  Google Scholar 

  9. Saravanan, D.: Effective video data retrieval using image key frame selection. In: Advances in Intelligent Systems and computing, pp. 145–155 (2017)

    Google Scholar 

  10. Saravanan, D.: Clustering the irregularity events in intelligence surrounding systems. J. Pure Appl. Math. 119(12), 15025–15035 (2018) (Special Issues), ISSN:1311-8080

    Google Scholar 

  11. Fan, J., Luo, H.: Emantic video classification by integrating flexible mixture model with adaptive em algorithm. In: ACMSIGMM, pp. 9–16 (2003)

    Google Scholar 

  12. Wang. J.Z.: A text book on. In: Integrated Region-Based Image Retrieval. Kluwer Academic Publishers (2001)

    Google Scholar 

  13. Zhang, J., Hsu, W., Lee, M.L.: An information driven framework for image mining. In: Proceedings of 12th International Conference on Database and Expert Systems Applications (DEXA). Munich, Germany (2001)

    Google Scholar 

  14. Saravanan, D.: Effective video content retrieval using image attributes. EAI Endorsed Trans. Energy Web Inf. Technol. 5(18), e8, 1–5 (2018)

    Google Scholar 

  15. Saravanan, D.: Efficient video indexing and retrieval using hierarchical clustering techniques. Adv. Intell. Syst. Comput. 712, 1–8 (2018). ISBN:978-981-10-8227

    Google Scholar 

  16. Vailaya, A., Figueiredo, M., Jain, A.K., Zhang, H.J.: Image classification for content-based indexing. IEEE Trans. Image Process. 10(1), 117–130 (2001)

    Article  Google Scholar 

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Saravanan, D., Joseph, D., Vaithyasubramanian, S. (2020). Effective Utilization of Image Information Using Data Mining Technique. In: Balas, V., Kumar, R., Srivastava, R. (eds) Recent Trends and Advances in Artificial Intelligence and Internet of Things. Intelligent Systems Reference Library, vol 172. Springer, Cham. https://doi.org/10.1007/978-3-030-32644-9_22

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