Nikola Zaric

An Application of Multidimensional Time-Frequency Analysis as a Base for the Unified Watermarking Approach

A watermarking approach based on multidimensional time-frequency analysis is proposed. It represents a unified concept that can be used for different types of data such as audio, speech signals, images or video. Time-frequency analysis is employed for speech signals, while space/spatial-frequency analysis is used for images. Their combination is applied for video signals. Particularly, we focus on the 2-D case: space/spatial-frequency based image watermarking procedure that will be subsequently extended to video signal. A method that selects coefficients for watermarking by estimating the local frequency content is proposed. In order to provide watermark imperceptibility, the nonstationary filtering is used to model the watermark which corresponds to the host signal components. Furthermore, the watermark detection within the multidimensional time-frequency domain is proposed. The efficiency and robustness of the procedure in the presence of various attacks is proven experimentally.

An Implementation of the L-Estimate Distributions for Analysis of Signals in Heavy-Tailed Noise

An analog-digital system for implementation of the robust time-frequency distributions is proposed. It provides an efficient real-time analysis of nonstationary signals corrupted by heavy-tailed noise. The most important part of this system is the realization of the L-estimate short-time Fourier transform that requires sorting operation. The proposed solution is designed to execute sorting operation within a single clock cycle, regardless of the number of inputs. The performance of the proposed hardware is tested on a real signal example.

Robust watermarking procedure based on JPEG discrete cosine transform image compression

A new procedure for watermarking in the 88 block- based discrete cosine transform (DCT) domain (used for JPEG compression) is proposed. The influence of JPEG quantization on watermarked coefficients and on watermark is considered. The cri- terion for coefficients selection is derived, providing robustness for an arbitrary quantization degree. The modified form of coefficients probability density function (pdf) leads to the class of modified opti- mal detectors. Theoretical results are illustrated on various ex- amples. Efficiency of the proposed procedure is shown in the pres- ence of different quantization degrees, and other common attacks.

A multiwindow time-frequency approach based on the concepts of robust estimate theory

An approach to multiwindow time-frequency analysis that provides robust performance in noisy environment is proposed. The concept of robust estimates of instantaneous frequency is used to define the optimal weighting coefficients for the multiwindow spectrogram. The proposed form of multiwindow spectrogram provides improved instantaneous frequency estimation for nonstationary signals in the presence of additive Gaussian noise. The efficiency of the proposed approach is tested in the experiments.

An Approach to Digital Watermarking of Speech Signals in the Time-Frequency Domain

A watermarking scheme in the time-frequency domain is proposed. The region for watermark embedding is selected by using the S-method based on the time-frequency representation. Time-varying filter scheme is used to map the watermark sequence from the time-frequency domain to the time domain. Watermark detection is performed in the time-frequency domain. Theory is illustrated by the example

Automated algorithm for classification of water-flow signals to support Ambient Assisted Living applications

Characterization of a home water-flow signal, as an outcome of an analysis of the most appropriate representation in time, frequency and time-frequency domain, has not been adequately studied; mainly due to lack of such specific need. Nevertheless, being able to characterize a water-flow signal in the home-environment can support Ambient Assisted Living systems to determine the activity of a senior citizen, thus contributing to the daily pattern recognition, as well as to identify critical situation. This has triggered our research activities to develop an automated decision-making algorithm for detection of different water-flows that may be found in an ordinary bathroom. The preliminary results will be presented in this paper. The time-frequency representations are employed to analyze and characterize different water-flow signals, as well as to provide input parameters for the algorithm. These approach and algorithm can be used in numerous applications where automated decision-making scenario is required.

Ambient assisted living systems in the context of human centric sensing and IoT concept: EWall case study

This paper proposes the concept of Human Centric Sensing in the context of Internet of Things and Ambient Assisted Living. The paper uses a case study to present and analyze the proposed idea, and identifies the main challenges and open issues that require research and policy attention.

Low cost intelligent notification and alarming system for ambient assisted living applications

In this paper we will propose a solution for home setup of sensors and actuators that are required for appropriate functioning of any Ambient Assisted Living application. The proposed installation solution is low cost, easy to install, modular and reliable. Detailed analysis of sensor states is performed as well as analysis of different in home scenarios. Additionally an algorithm for Intelligent Notification and Alarming System for analysing data acquired from the sensors is proposed as well. The presented system may represent a good starting point for further elaboration and exploitation.