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Abstract:Watermarking is one of the efficient approaches for digital authentication. An adaptive feature point extraction model is proposed in this paper for robust watermarking. The host image is treated with number of geometric attacks for extracting the consistent feature points form the image. The proposed watermarking scheme follows the adaptive feature point extraction method to retrieve the feature points from the host image. The response value of the feature points is calculated for improving the selection of feature points. The watermark insertion procedure is employed by inserting the watermarking bits with in the place of feature points. The feature point portion is extracted from the image and replaces the portion with watermarking bits. The watermark extraction procedure is used to restore the original image from the watermarked image. The watermarking bits in the image are replaced by the feature point portion for restoring the original image. The simulation experiment is carried with the MATLAB simulator. The proposed algorithm is tested with geometric attacks such as scaling, rotation, noise pollution and JPEG compression. The proposed method proved its efficiency when compared to other remaining algorithms.

A rule-based system is a set of "if-then" statements that uses a set of assertions, to which rules on how to act upon those assertions are created. Rule-based expert systems have played an important role in modern intelligent systems and their applications in strategic goal setting, planning, design, scheduling, fault monitoring, diagnosis, and so on. The theory of decision support system is explained in detail. This chapter explains how the concepts of fuzzy logic are used for forward and backward chaining. Patient data is analyzed with the help of inference rules.

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In today’s world, the transmission of secured and noiseless image is a difficult task. Therefore, effective strategies are important to secure the data or secret image from the attackers. Besides, denoising approaches are important to obtain noise-free images. For this, an effective crypto-steganography method based on Lightweight Encryption Algorithm (LEA) and Modified Least Significant Bit (MLSB) method for secured transmission is proposed. Moreover, a bilateral filter-based Whale Optimization Algorithm (WOA) is used for image denoising. Before image transmission, the secret image is encrypted by the LEA algorithm and embedded into the cover image using Discrete Wavelet Transform (DWT) and MLSB technique. After the image transmission, the extraction process is performed to recover the secret image. Finally, a bilateral filter-WOA is used to remove the noise from the secret image. The Verilog code for the proposed model is designed and simulated in Xilinx software. Finally, the simulation results show that the proposed filtering technique has superior performance than conventional bilateral filter and Gaussian filter in terms of Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM).