References
[1]. Bartolini, I., Ciaccia, P., & Waas, F. (2001, September). Feedback Bypass: A new approach to interactive similarity th query processing. In Proceedings of the 27th Very Large Data Base (VLDB) (pp. 201-210).
[2]. Brunelli, R., & Mich, O. (2000). Image retrieval by examples. IEEE Transactions on Multimedia, 2(3), 164-171. https://doi.org/10.1109/6046.865481
[3]. Chen, L., Özsu, M. T., & Oria, V. (2004). MINDEX: An efficient index structure for salient-object-based queries in video databases. Multimedia Systems, 10(1), 56-71. https://doi.org/10.1007/s00530-004-0137-4
[4]. Fayyad, U. M., Djorgovski, S. G., & Weir, N. (1996). Automating the analysis and cataloging of sky surveys. In Advances in Knowledge Discovery and Data Mining (pp. 471-493).
[5]. Liu, Y., Zhang, D., Lu, G., & Ma, W. Y. (2007). A survey of content-based image retrieval with high-level semantics. Pattern Recognition, 40(1), 262-282. https://doi.org/10. 1016/j.patcog.2006.04.045
[6]. Ma, W. Y., & Manjunath, B. S. (1997). Netra: A toolbox for navigating large image databases. In Proceedings of International Conference on Image Processing (pp. 568- 571). https://doi.org/10.1109/ICIP.1997.647976
[7]. Pentland, A., Picard, R. W., & Sclaroff, S. (1996). Photobook: Content-based manipulation of image databases. International Journal of Computer Vision, 18(3), 233-254. https://doi.org/10.1007/BF00123143
[8]. Saravanan, D. (2017a). Video data image retrieval using–BRICH. World Journal of Engineering, 14(4), 318-323. https://doi.org/10.1108/WJE-09-2016-0093
[9]. Saravanan, D. (2017b). Clustering of video in formations using BRICH Methodology. Pakistan Journal of Biotechnology, 14(2), 377-380.
[10]. Saravanan, D. (2017c). Effective video data retrieval using image key frame selection. In Proceedings of the First International Conference on Computational Intelligence and Informatics (pp. 145-155). Singapore: Springer. https:// doi.org/10.1007/978-981-10-2471-9_15
[11]. Saravanan, D. (2018a). Image frame mining using indexing technique. In Data Engineering and Intelligent Computing (pp. 127-137). Singapore: Springer. https://doi. org/10.1007/978-981-10-3223-3_12
[12]. Saravanan, D. (2018b). Effective video content retrieval using image attributes. EAI Endorsed Transactions on Energy Web and Information Technologies, 5(18), 1-5. https://doi.org/10.4108/eai.12-6-2018.154818
[13]. Saravanan, D. (2018c). Efficient video indexing and retrieval using hierarchical clustering technique. In Proceedings of the Second International Conference on Computational Intelligence and Informatics (pp. 1-8). Singapore: Springer. https://doi.org/10.1007/978-981-10-8 228-3_1
[14]. Saravanan, D. (2019a). Image substance extraction using data mining clustering method. International Journal of Innovative Technology and Exploring Engineering (IJITEE), 9(2), 2735-2739.
[15]. Saravanan, D. (2019b). Information retrieval using image attribute possessions. In Wang J., Reddy G., Prasad V., Reddy V. (Eds.) Soft Computing and Signal Processing (pp 759-767). Advances in Intelligent Systems and Computing, Vol 898. Springer, Singapore. https://doi.org/ 10.1007/978-981-13-3393-4_77
[16]. Saravanan, D., & Joseph, D. (2019). Image data extraction using image similarities. In Panda G., Satapathy S., Biswal B., Bansal R. (Eds.) Microelectronics, Electromagnetics and Telecommunications (pp. 409- 420). Lecture Notes in Electrical Engineering, Vol 521. Springer, Singapore. https://doi.org/10.1007/978-981-13- 1906-8_43
[17]. Stolorz, P., Nakarmura, H., Mesrobian, E., Muntz, R. R., Shek, E. C., Santos, J. R., ... & Farrar, J. D. (1995). Fast spatio-temporal data mining of large gelphysical database. KDD-95 Proceedings (pp. 300-305).
