Applications of the naturalness preserving transform to image watermarking and data hiding

In this paper, a saliency and phase congruency based digital image watermarking scheme has been projected. The planned technique implants data at least significant bits (LSBs) by means of adaptive replacement. Here more information is embedded into less perceptive areas within the original image determined by a combination of spectral residual saliency map and phase congruency map. The position of pixels with less perceptibility denotes the most unimportant region for data hiding from the point of visibility within an image. Therefore any modification within these regions will be less perceptible to one observer. The model gives a concept of the areas which has excellent data hiding capacity within an image. Superiority of the algorithm is tested through imperceptibility, robustness, along with data hiding capacity.

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A Comprehensive Approach to Image Watermarking, Encryption and Steganography

Computer and Information Science ◽

10.5539/cis.v8n4p32 ◽

2015 ◽

Vol 8 (4) ◽

pp. 32

Author(s):

Sabarish Sridhar

Keyword(s):

Data Hiding ◽

Data Transmission ◽

Mean Squared Error ◽

Signal To Noise Ratio ◽

Image Watermarking ◽

Cover Image ◽

Second Step ◽

Squared Error ◽

Feature Similarity ◽

Secure Data Transmission

Steganography, water marking and encryption are widely used in image processing and communication. A general practice is to use them independently or in combination of two - for e.g. data hiding with encryption or steganography alone. This paper aims to combine the features of watermarking, image encryption as well as image steganography to provide reliable and secure data transmission .The basics of data hiding and encryption are explained. The first step involves inserting the required watermark on the image at the optimum bit plane. The second step is to use an RSA hash to actually encrypt the image. The final step involves obtaining a cover image and hiding the encrypted image within this cover image. A set of metrics will be used for evaluation of the effectiveness of the digital water marking. The list includes Mean Squared Error, Peak Signal to Noise Ratio and Feature Similarity.

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An Advanced Reversible Data Hiding Algorithm Using Local Similarity, Curved Surface Characteristics, and Edge Characteristics in Images

Applied Sciences ◽

10.3390/app10030836 ◽

2020 ◽

Vol 10 (3) ◽

pp. 836 ◽

Cited By ~ 1

Author(s):

Soo-Mok Jung ◽

Byung-Won On

Keyword(s):

Data Hiding ◽

Reversible Data Hiding ◽

Image Watermarking ◽

Surface Characteristics ◽

Cover Image ◽

Curved Surface ◽

Local Similarity ◽

Stego Image ◽

Confidential Data ◽

The Difference

In this paper, we proposed methods to accurately predict pixel values by effectively using local similarity, curved surface characteristics, and edge characteristics present in an image. Furthermore, to hide more confidential data in a cover image using the prediction image composed of precisely predicted pixel values, we proposed an effective data hiding technique that applied the prediction image to the conventional reversible data hiding technique. Precise prediction of pixel values greatly increases the frequency at the peak point in the histogram of the difference sequence generated using the cover and prediction images. This considerably increases the amount of confidential data that can be hidden in the cover image. The proposed reversible data hiding algorithm (ARDHA) can hide up to 24.5% more confidential data than the existing algorithm. Moreover, it is not possible to determine the presence of hidden confidential data in stego-images, as they possess excellent visual quality. The confidential data can be extracted from the stego-image without loss, and the original cover image can be restored from the stego-image without distortion. Therefore, the proposed algorithm can be effectively used in digital image watermarking, military, and medical applications.

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