Piotr Lipiński

Improving watermark resistance against removal attacks using orthogonal wavelet adaptation

This paper proposes a new approach for enhancing the robustness of wavelet-based image watermarking algorithms. The method adjusts wavelet used in the process of image watermarking in order to maximize resistance against image processing operations. Effectiveness of the approach is demonstrated using blind multiplicative watermarking algorithm, but it can easily be generalized to all wavelet-based watermarking algorithms. Presented results demonstrate that wavelets generated using proposed approach outperform other wavelet bases commonly used in image watermarking in terms of robustness to removal attacks.

Efficient 1D and 2D Daubechies Wavelet Transforms with Application to Signal Processing

In this paper we have introduced new, efficient algorithms for computing one- and two-dimensional Daubechies wavelet transforms of any order, with application to signal processing. These algorithms has been constructed by transforming Daubechies wavelet filters into weighted sum of trivial filters. The theoretical computational complexity of the algorithms has been evaluated and compared to pyramidal and ladder ones. In order to prove the correctness of the theoretical estimation of computational complexity of the algorithms, sample implementations has been supplied. We have proved that the algorithms introduced here are the most robust of all class of Daubechies transforms in terms of computational complexity, especially in two dimensional case.

Transformer Monitoring System Taking Advantage of Hybrid Wavelet Fourier Transform

In this paper, the power transformer monitoring system (PTMS), which uses expert database to detect failures and hybrid wavelet-fourier transform (HWFT) to compress data is introduced. The HWFT takes advantage of both: discrete wavelet transform (DWT) and discrete cosine transform (DCT), to compress data. It has been proved that HWFT outperforms DCT and DWT, which are used in JPEG and JPEG2000 compression standards, in terms of compression ratio while preserves the same accuracy of decompressed signal.

Digital watermarking enhancement using wavelet filter parametrization

In this paper a genetic-based enhancement of digital image watermarking in the Discrete Wavelet Transform domain is presented. The proposed method is based on adaptive synthesis of a mother wavelet used for image decomposition. Wavelet synthesis is performed using parametrization based on an orthogonal lattice structure. A genetic algorithm is applied as an optimization method to synthesize a wavelet that provides the best watermarking quality in respect to the given optimality criteria. Effectiveness of the proposed method is demonstrated by comparing watermarking results using synthesized wavelets and the most commonly used Daubechies wavelets. Experiments demonstrate that mother wavelet selection is an important part of a watermark embedding process and can influence watermarking robustness, separability and fidelity.

Expert Systems in the Medical Insurance Industry

Here we have described the expert system for the medical insurance industry which has been developed at the Collage of Computer Science in cooperation with Technical University of Lodz. The system has been implemented and tested in an insurance company. The system reduces resources, costs and improves reliability of the insurance decision-making process. The time required to insure a customer has been reduced by eight times. The system is an ideal teacher for beginners, and can be used when educating new employees.

Image segmentation method using wavelet transform

This article deals with a method of image segmentation basing on wavelet transforms. A test image covered with areas of different textures is considered. Segmentation results are presented and discussed.

Modeling the processes of dynamics at biogas plants on the acetogenesis stage

The task of modeling the processes of anaerobic microbiological fermentation with keeping the balance at the acetogenesis stage was considered in this work. It was proposed and justified to build models at these stages in the form of interval discrete dynamic model. The structure identification method of IDDM on the principles of honey bee colony functioning in the food search process, which provides the possibility of obtaining simple IDDDM structures with specified prognostic properties relative to existing methods, was substantiated.

Information Platform TEWI

Information Platform TEWI (Technology, Education and Research, Knowledge, Innovation) is an interregional research network, which aims at integrating Polish scientific community using Product Lifecycle Management software. It is being created by three universities: Technical University of Lodz, Warsaw University of Technology and Bialystok University of Technology. The platform TEWI will allow to take advantage of new information technologies and state of the art solutions in research and industry. It will facilitate cooperation between the universities and industry by utilizing compatible software. The Product Lifecycle Management software will make knowledge management easier and more available for scientists. Moreover, the new software will improve the skills of scientific community and make the technology transfer to the industry more fluent. As a result this should make the Polish industry more competitive.

Towards Modern Collaborative Knowledge Sharing Systems

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