45 research outputs found

    Towards New Classes of Intelligent Cognitive Information Systems for Semantic Pattern Classification

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    This paper introduces two new classes of specialised vision systems called UBIAS and E-UBIAS. Such systems belong to the group of cognitive reasoning systems and are designed for the semantic analysis of visual patterns in the form of medical images. Proposed systems are predecessors of a new generation of intelligent systems dedicated for understanding medical diagnostic visualization and using this data as biometric characteristics

    Security issues on digital watermarking algorithms

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    This paper gives a general introduction to the digital watermarking procedures and their security aspects. The first issue is to clarify unifying and differentiating properties of steganography and watermarking. Then the most important aspects of digital watermarking are reviewed by studying application, requirement and design problems. We put emphasis on the importance of digital watermark as an effective technology to protect intellectual property rights and legitimate use of digital images. In the paper we provide an overview of the most popular digital watermarking methods for still images available today. The watermarking algorithms are divided into two major categories of spatial and transform domains. Because of outstanding robustness and imperceptibility the transform domain algorithms are the mainstream of research. Popular transforms of images include the DFT (Discrete Fourier Transform) ([1, 2, 3, 4, 5]), DCT (Discrete Cosine Transform) ([1, 3, 6, 5]) and DWT (Discrete Wavelet Transform) ([1, 3, 4, 7, 6, 5]). In the paper we emphasize the advantageous features of DWT such as local time-frequency and multi-scale analysis, preserving the quality of host image and ensuring high robustness of watermark. Finally, we present three algorithms which are based on the combination of DWT and some other transformations like DFT ([4]), DCT ([6]) and the Arnold transform ([7, 6]). Finally, we discuss security requirements and possible attacks on the watermarking systems

    Advances in Cognitive Information Systems

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    The development of computer science is now so rapid that we, the readers, in-creasingly receive technology news about new solutions and applications which very often straddle the border between the real and the virtual worlds. Computer science is also the area in which cognitive science is witnessing a renaissance, be-cause its combination with technical sciences has given birth to a broad scientific discipline called cognitive informatics. And it is this discipline which has become the main theme of this monograph, which is also to serve as a kind of guide to cognitive informatics problems. This book is the result of work on systems for the cognitive analysis and inter-pretation of various data. The purpose of such an analytical approach is to show that for an in-depth analysis of data, the layers of semantics contained in these sets must be taken into account. The interdisciplinary nature of the solutions proposed means that the subject of cognitive systems forming part of cognitive informatics becomes a new challenge for the research and application work carried out. The authors of this monograph hope that it will guide Readers on an interesting and accurate journey through the intricacies of information and cognitive science

    Strategic Information Splitting Using Biometric Patterns

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    Abstract In this paper will be proposed a new algorithm for secure strategic information sharing using biometric information. In classic cryptographic threshold schemes used for secret splitting and sharing there aren't any connection between generated shares and particular participants of threshold protocol. In fact sometimes it may be useful to generate a special personalized shadows, which allow not only reveal the original secret information, but also to identify who is the owner of particular shares or information shadow

    Intelligent Data Management and Security in Cloud Computing

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    This paper will present the authors’ own techniques of secret data management and protection, with particular attention paid to techniques securing data services. Among the solutions discussed, there will be information-sharing protocols dedicated to the tasks of secret (confidential) data sharing. Such solutions will be presented in an algorithmic form, aimed at solving the tasks of protecting and securing data against unauthorized acquisition. Data-sharing protocols will execute the tasks of securing a special type of information, i.e., data services. The area of data protection will be defined for various levels, within which will be executed the tasks of data management and protection. The authors’ solution concerning securing data with the use of cryptographic threshold techniques used to split the secret among a specified group of secret trustees, simultaneously enhanced by the application of linguistic methods of description of the shared secret, forms a new class of protocols, i.e., intelligent linguistic threshold schemes. The solutions presented in this paper referring to the service management and securing will be dedicated to various levels of data management. These levels could be differentiated both in the structure of a given entity and in its environment. There is a special example thereof, i.e., the cloud management processes. These will also be subject to the assessment of feasibility of application of the discussed protocols in these areas. Presented solutions will be based on the application of an innovative approach, in which we can use a special formal graph for the creation of a secret representation, which can then be divided and transmitted over a distributed network

    Insider Threats and Cryptographic Techniques in Secure Information Management

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    FITTING OF TONAL CURVE AND BALANCING OF GRAY LEVELS IN CONTRAST EXPANSION AND PRELIMINARY IMAGING OF STRUCTURES IN THE ANALYSIS

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    The article presents a group of transformations which medical pictures can be subjected to, in the aim of enhancing their contrast and better distinguishing and diagnosis of organs shown in this pictures. In this work the analysis was based on images ac膮uired by various techni膮ues, such as roentgenography (RTG), magnetic resonance (MRI), classic Computer tomography (CT) and ultrasonography (USG). Contrast expansion in these images was performed using the histogram mcthod of balancing of gray levels and the method based on the modification of tonal curve. Such transformations were necessary during preliminary processing of these images, especially to adjust their quality for next steps of the analysis in case of automatic medical diagnosis, and also to enable their visua! evaluation by specialists and diagnostic interpretation of images of or颅 gans and their structural features. The studies show that the method based on the modification of tonal curve yields better results in case of images ac膮uired by roentgenography and magnetic re颅 sonance imaging. On the other hand, histogram method is mor臋 suitable for contrast expansion in CT and USG images

    Fitting of Tonal Curve and Balancing of Gray Levels in Contrast Expansion and Preliminary Imaging of Structures in the Analysis of Medical Pictures

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    The article presents a group of transformations which medical pictures can be subjected to, in the aim of enhancing their contrast and better distinguishing and diagnosis of organs shown in this pictures. In this work the analysis was based on images acquired by various techniques, such as roentgenography (RTG), magnetic resonance (MRI), classic computer tomography (CT) and ultrasonography (USG). Contrast expansion in these images was performed using the histogram method of balancing of gray levels and the method based on the modification of tonal curve. Such transformations were necessary during preliminary processing of these images, especially to adjust their quality for next steps of the analysis in case of automatic medical diagnosis, and also to enable their visual evaluation by specialists and diagnostic interpretation of images of organs and their structural features. The studies show that the method based on the modification of tonal curve yields better results in case of images acquired by roentgenography and magnetic resonance imaging. On the other hand, histogram method is more suitable for contrast expansion in CT and USG images

    Methods of the Straightening Transformation and Analysis of Outer Contours of Objects in Medical Image Recognitio

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    One of the most important problems appearing in computer systems for the recognition and analysis of medical images, supporting diagnostics and medical therapy, is the processing of obtained images or their series in such a way that it is possible to unambiguously determine the disease symptoms occurring in them. Based on the detected symptoms, it is then possible to identify various disease entities, which in turn is the starting point for planning further therapy. Characterizing the process of automatic medical diagnostics, it can be stated that information in computer diagnostic systems can come from data on the occurrence of disease symptoms obtained during the analysis of medical images thanks to the use of various methods of artificial intelligence. Where subjected to recognition there are images on which any morphological changes of any of the organs can be observed, i.e. in the recognition of diseases visible on images obtained by various computed tomography techniques or radiographic images (e.g. ERCP, angiograms), the purpose of analyzing such images is to identify and unequivocal recognition of such morphological changes occurring in the examined organ. To this end, syntactic image recognition methods are often used. However, before proceeding to the proper extraction of the sought-after features that indicate the occurrence of disease symptoms, it is usually necessary to pre-process the analyzed photos so as to improve their quality, remove unnecessary (from the point of view of the diagnosis made) details while separating the recognized objec
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