The main aim of the image segmentation is to change the representation of the image so that the boundaries and objects in an image can be easily observed. In this study, a novel algorithm is proposed for the image segmentation using gray scale images. The codebook algorithm is used in the proposed approach for optimal multidirectional thresholding approach. The background and foreground pixel values are stored in the codebook. It uses standard deviations along the four directions to search the background and foreground pixels iteratively. The misclassification error and Jaccard index are used to measure the system efficiency. The mean of misclassification error is 95.80% with standard deviation of 1.91 and the mean of Jaccard index is 92.36% with standard deviation of 5.6. These measures shows the efficacy of the proposed system.

The user is enabled by means of Cloud Computing (CC) to store and access the data as of anywhere. To secure the data amassed on the Cloud Server (CS), CC security encompasses a collection of policies and technologies. Most existing methods bring about a lower-Security Level (SL), the higher computation time for encryption together with decryption, and also Memory Usage (MU) issues, et cetera. Here, to resolve such issues in the existent methods, an effectual modified cryptographic is proposed in favor of the secured Data Storage (DS) in CC. Firstly, secure authentication is done via the Alder32 hash algorithm. The user is authenticated via registration, login, together with verification. Subsequently, the authenticated user commences uploading the file. Prior to uploading, the inputted file is bifurcated into sub-files counting on the size, and the features are extracted as of the split file and distributed CS. Next, the Brownian Motion-based BAT algorithm (BM-BAT) selects the appropriate distributed CS. Then, the Modified Cryptographic (XOR-MECC) uploads the files securely into the CS. The experimentation's outcomes state that the proposed work attains better performance when weighed against the prevailing works.