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User Interface Using WWW for Photo Image Analysis
Balcárek, Lukáš ; Láník, Aleš (referee) ; Zemčík, Pavel (advisor)
This master's thesis deals with the user interface for machine quality assessment of the technical groups of photos. This work is written about photos, graphics editors and their evaluation. The practical part is focused on the design and creation of application with web user interface, which evaluates and compares the quality of photos. Finally is this created application with its user interface tested by users, its benefits and opportunities for further expansion are evaluated.
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Optical character recognition from image data
Marinič, Michal ; Uher, Václav (referee) ; Burget, Radim (advisor)
The thesis is concerned with optical character recognition from image data with different methods used for character classification. In the first theoretical part it focuses on explanation of all important parts of system for optical character recognition. The latter practical part of the thesis describes an example of image segmentation, the implementation of artificial neural networks for image recognition and create simple training set of data for the evaluation of the network. It also describes the process of training Tesseract tool and its implementation in a simple application EasyTessOCR for character recognition.
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User Interface Using WWW for Photo Image Analysis
Balcárek, Lukáš ; Láník, Aleš (referee) ; Zemčík, Pavel (advisor)
This master's thesis deals with the user interface for machine quality assessment of the technical groups of photos. This work is written about photos, graphics editors and their evaluation. The practical part is focused on the design and creation of application with web user interface, which evaluates and compares the quality of photos. Finally is this created application with its user interface tested by users, its benefits and opportunities for further expansion are evaluated.
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Optical character recognition from image data
Marinič, Michal ; Uher, Václav (referee) ; Burget, Radim (advisor)
The thesis is concerned with optical character recognition from image data with different methods used for character classification. In the first theoretical part it focuses on explanation of all important parts of system for optical character recognition. The latter practical part of the thesis describes an example of image segmentation, the implementation of artificial neural networks for image recognition and create simple training set of data for the evaluation of the network. It also describes the process of training Tesseract tool and its implementation in a simple application EasyTessOCR for character recognition.
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