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Automated Scene Surveillance using Frame Propagation from Massive Sequencization Fusion of Frame Imaging

Ankush Rai


Remote sensing scene surveillance has already become significant contributions to many areas such; as environmental engineering and civil applications. However, these fields are still deprived from completely being automated. Since, decisions based on surveillance and sensing data in these fields strongly depend on the accuracy of these data but yet such data is produced by a measuring device and additionally being deprived from effective models and thus being generally prone to imperfection such uncertainty, imprecision, and ignorance leading to unnecessary elimination of useful data . Therefore, in the present study we've proposed an algorithm for automated scene surveillance with accurate image processing and massive sequencized fusing of frame images.

Keywords: Prediction, scene surveillance, imaging

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Aksoy S., Cinbis R. G. Image Mining using Directional Spatial Constraints, IEEE Geosci. Remot. Sens. Lett. 2010; 7(1): 33–37p.

Hubert-Moy, Corgne L., Mercier S., et al. Land Use and Land Cover Change Prediction with the Theory of Evidence: A Case Study in an Intensive Agricultural Region of France, Fifth International Conference on Information Fusion, 2002,114–121p.

Boulila W., Farah I. R., Ettabaa K. S., et al. A Data Mining based Approach to Predict Spatio-temporal Changes in Satellite Images, Int. J. Appl. Earth 2011; 13(3): 386–395p.

Boulila W., Farah I. R., Ettabaa K. S., et al. Combining Decision Fusion and Uncertainty Propagation to Improve Land Cover Change Prediction in Satellite Image Databases, J. Multimedia Process. Technol. 2011; 2(3): 127–139p.

Boulila W., Farah I. R., Ettabaa K. S., et al. Spatiotemporal Modeling for Knowledge Discovery in Satellite Image Databases, CORIA 2010: Conference en Recherche d’Information et Applications, Sousse, 2010, 35–49p.


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