Features Analysis and Extraction Techniques for the Image Steganography
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Abstract
The image stenography is utilized to provide security to sensitive data. Several techniques are planned so far for creating an effective stegno image. The existing technique makes the utilization of discrete wavelet transform for detecting the edges from the images and the final stegno image is produced by inserting text on the detected edges. This research work deploys the Grey Scale Co-occurrence Matrix (GLCM) to create the stegno image so that the attributes can be extracted. The text is inserted into the image using PCA (Principal Component Analysis). MATLAB is applied to test the performance of suggested model. The testing depicts that the suggested model provides efficient performance concerning PSNR (Peak signal-to-noise ratio) and MSE (mean squared error).
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