Informatica

Clinics and hospitals have already adopted more technological resources to provide a faster and more precise diagnostic for patients, health care providers, and institutes of medicine. Security issues get more and more important in medical services via communication resources such as Wireless-Fidelity (Wi-Fi), third generation of mobile telecommunications technology (3G), and other mobile devices to connect medical systems from anywhere. Furthermore, cloud-based medical systems allow users to access archived medical images from anywhere. In order to protect medical images, lossless data hiding methods are efficient and easy techniques. In this paper, we present a data hiding of two-tier medical images based on histogram shifting of prediction errors. The median histogram shifting technique and prediction error schemes as the two-tier hiding have high capacity and PSNR in 16-bit medical images.

Data hiding technique is an important multimedia security technique and has been applied to many domains, for example, relational databases. The existing data hiding techniques for relational databases cannot restore raw data after hiding. The purpose of this paper is to propose the first reversible hiding technique for the relational database. In hiding phase, it hides confidential messages into a relational database by the LSB (Least-Significant-Bit) matching method for relational databases. In extraction and restoration phases, it gets the confidential messages through the LSB and LSB matching method for relational databases. Finally, the averaging method is used to restore the raw data. According to the experiments, our proposed technique meets data hiding requirements. It not only enables to recover the raw data, but also maintains a high hiding capacity. The complexity of our algorithms shows their efficiencies.

Scalar quantizer selection for processing a signal with a unit variance is a difficult problem, while both selection and quantizer design for the range of variances is even tougher and to the authors’ best knowledge, it is not theoretically solved. Furthermore, performance estimation of various image processing algorithms is unjustifiably neglected and there are only a few analytical models that follow experimental analysis. In this paper, we analyse application of piecewise uniform quantizer with Golomb-Rice coding in modified block truncation coding algorithm for grayscale image compression, propose design improvements and provide a novel analytical model for performance analysis. Besides the nature of input signal, required compression rate and processing delay of the observed system have a strong influence on quantizer design. Consequently, the impact of quantizer range choice is analysed using a discrete designing variance and it was exploited to improve overall quantizer performance, whereas variable-length coding is applied in order to reduce quantizer’s fixed bit-rate. The analytical model for performance analysis is proposed by introducing Inverse Gaussian distribution and it is obtained by discussing a number of images, providing general closed-form solutions for peak-signal-to-noise ratio and the total average bit-rate estimation. The proposed quantizer design ensures better performance in comparison to the other similar methods for grayscale image compression, including linear prediction of pixel intensity and edge-based adaptation, whereas analytical model for performance analysis provides matching with the experimental results within the range of 1 dB for PSQNR and 0.2 bpp for the total average bit-rate.

This paper proposes a reversible data hiding method for error diffused halftone images. It employs statistics feature of pixel block patterns to embed data, and utilizes the HVS characteristics to reduce the introduced visual distortion. The watermarked halftone image can be perfectly recovered if it is intact, only a secret key is required. The method is suitable for the applications where the content accuracy of the original halftone image must be guaranteed, and it is easily extended to the field of halftone image authentication.

The hierarchical principle of video-information analysis (progressive detalisation) is one from the set of principles which are implemented in the living vision system. The reflection of this principle in the techniques of the representation of a shape of the region, occupied by binary image, allows us to find a solution of two tasks simultaneously: data compression and data structure, which suits for geometric transformations of the image. This report includes operations which are performed on the hierarchical list of rectangles. The latter is built up by using intermediate pyramidal representation.