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Steganography
Podhorský, Jiří ; Kubíček, Radek (referee) ; Zemčík, Pavel (advisor)
This bachelor project focuses on steganography and presents new modifications of known metods steganography and their implementation. It also presents implementation of adaptive metod Neighbours, for comparison. Both of the metods are based on the "Least Significant Bit" exploitation. It is also demonstrated that newly proposed modification can be used in other metods of steganography. The purpose of proposed method is to encode a secret information into the digital image so that the information is not easily detectable.
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Detect the Use of Retouch Filters in a Face Image
Kraváček, Adam ; Drahanský, Martin (referee) ; Goldmann, Tomáš (advisor)
These days, altering images via filters is one of the easiest ways of enhancing its properties. Social networks like Instagram or Snapchat, focused primarily on image sharing, offer their users the option to apply filters on their images, which alter their colours to make them look better. If someone was to extract images from these platforms, many of these images would have a filter applied. This thesis explains the principles of these filters and focuses on detection of filters on facial images. Several approaches to detecting filters are being experimented with. Detection by analysis of histograms and detection by convolutional neural network achieve the best results and so are implemented in a program with a simple user interface. They achieved a success rate of 94,44% (histogram) and 99,10% (CNN). This thesis also investigates the impact of filters on facial recognition, where the impact varies depending on the filter used. Some filters have a significant impact on the rate of successful identifications, whereas others have little impact.In general, however, it can be said that the changes introduced by the application of filters are not negligible.
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Detect the Use of Retouch Filters in a Face Image
Kraváček, Adam ; Drahanský, Martin (referee) ; Goldmann, Tomáš (advisor)
These days, altering images via filters is one of the easiest ways of enhancing its properties. Social networks like Instagram or Snapchat, focused primarily on image sharing, offer their users the option to apply filters on their images, which alter their colours to make them look better. If someone was to extract images from these platforms, many of these images would have a filter applied. This thesis explains the principles of these filters and focuses on detection of filters on facial images. Several approaches to detecting filters are being experimented with. Detection by analysis of histograms and detection by convolutional neural network achieve the best results and so are implemented in a program with a simple user interface. They achieved a success rate of 94,44% (histogram) and 99,10% (CNN). This thesis also investigates the impact of filters on facial recognition, where the impact varies depending on the filter used. Some filters have a significant impact on the rate of successful identifications, whereas others have little impact.In general, however, it can be said that the changes introduced by the application of filters are not negligible.
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Steganography
Podhorský, Jiří ; Kubíček, Radek (referee) ; Zemčík, Pavel (advisor)
This bachelor project focuses on steganography and presents new modifications of known metods steganography and their implementation. It also presents implementation of adaptive metod Neighbours, for comparison. Both of the metods are based on the "Least Significant Bit" exploitation. It is also demonstrated that newly proposed modification can be used in other metods of steganography. The purpose of proposed method is to encode a secret information into the digital image so that the information is not easily detectable.
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Bayesian classification of digital images by web application
Talich, M. ; Böhm, O. ; Soukup, Lubomír
The contribution introduces web application for image classification that has been developed at the Research Institute of Geodesy, Topography and Cartography in the framework of grant project InGeoCalc (supported by Ministry of education of the Czech Republic). The web application is aimed to display, examine and classify digital image data. The data are expected to be obtained from Internet by means of Web Map Services (WMS) or from other sources (possibly non-registered). Image data from different sources can be combined and presented as composition of layers (coverage) with adjustable degrees of transparency. After gathering the data, Bayesian (supervised) classification is applied to distinguish separate regions in the image. User can choose between several classification methods and adjust pertinent parameters. Furthermore, several subsequent basic analytical tools are offered, namely computation of distances, areas or perimeters related to the classified regions, simple statistical summaries about classification results (e.g. distribution of classes, percentage of non-classified regions, etc.). The classification results and registration parameters can be saved for further use. The web application is based on common Internet standards (HTML, Javascript, SVG). The only requirement for running the application is an up-to-date Internet browser supporting SVG (Scalable Vector Graphics). Typical usage of the web application can involve land cover mapping based on satellite or aerial images. The application is available free of charge for any Internet user.
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