Performance Analysis of Detection of Video for Secured Cloud Data Service
DOI:
https://doi.org/10.61841/zs4y2527Keywords:
Median Filter, Faster 2D-Otsu’s Segmentation, GLCM Feature, Multiclass Support Vector MachineAbstract
Identifying a malady could be critical to forestalling farming misfortunes. The objective of this paper is to make a computer-aided analysis to distinguish and classify the video frame analysis. This proposed identification look into includes video frame image acquisition, pre-processing, segmentation, extraction, and classification stages. The outline of the video is utilized to frame conversion. Four stages are utilized to recognize video. The initial step is preprocessing, and then segmentation utilized here is threshold-dependent segmentation of the faster 2D-Otsu. The subsequent stage is the extraction of the functionality, utilizing the GLCM tool. The third stage is that of description. Here the classifier for multiclass support vector machines (SVM) is utilized. And the last step is encryption. Here, the Tiny Encryption Algorithm (TEA) technique is used to encrypt data. The end encrypted output will be stored in the cloud. This technique is used to characterize the frame image on the video. The simulations are applied on MATLAB. Results of the experiment show the proposed efficiency of the device as compared to other methods of detection.
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