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Batch generation of graphical presentations
Semerák, Jakub ; Szőke, Igor (referee) ; Beran, Vítězslav (advisor)
This thesis describes design and implementation of system that allows batch generation of graphical presentations. The system also includes modules for image quality evaluation using no-reference blur metric and salient object detection. Selected methods for evaluation of image quality are described in detail and implemented in corresponding chapters, including proposed modifications and changes. Blur detection is based on wavelet transform, and salient object detection is achieved by investigating image contrast. Capabilities of these modules are evaluated on suitable image datasets.
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Camouflage pattern generator
Kremel, Tomáš ; Šejnoha, Jiří (advisor) ; Neruda, Roman (referee)
The thesis focuses on the visual camouflage generation problem characterised by cre- ating a colored pattern that, when printed on an object, has concealment capabilities. A good concealment can save lives of military personnel and protect important facilities. We approach the problem by devising a genetic algorithm with problem-specific ge- netic operators. The complexity of the algorihm lies in innovative utilization of the saliency predicting tool in the fitness operator. The construction of the operator con- nects human vision, image processing, deep learning and evolutionary computation. Along the computaionally costly fitness operator we suggest fast and simple concep- tually related trial operator we use for exploring characterics of the costly one. Then, we use this knowledge for generation of a camouflage pattern for forest environment. 1
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Batch generation of graphical presentations
Semerák, Jakub ; Szőke, Igor (referee) ; Beran, Vítězslav (advisor)
This thesis describes design and implementation of system that allows batch generation of graphical presentations. The system also includes modules for image quality evaluation using no-reference blur metric and salient object detection. Selected methods for evaluation of image quality are described in detail and implemented in corresponding chapters, including proposed modifications and changes. Blur detection is based on wavelet transform, and salient object detection is achieved by investigating image contrast. Capabilities of these modules are evaluated on suitable image datasets.
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