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Sensing eye movement using a device BIOPAC and eyetracker Pupil
Vančurová, Johana ; Mézl, Martin (referee) ; Svozilová, Veronika (advisor)
This bachelor thesis is focused on investigation of visual reaction time of driver using eye movements acquivition. Eye movements were acquired by Biopac device and eyetracker Pupil. The main aim of this work is to compare results of own experiments with points of reference. Theoretical part dealt with anatomy, physiology of eye and describing characteristics of EOG signals. Practical part included experimental measurements to which a group of probands was involved. In the last part of this work the obtained results were compared with the points of reference.
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Blood vessel segmentation in retinal image data
Vančurová, Johana ; Mézl, Martin (referee) ; Odstrčilík, Jan (advisor)
This master´s thesis deals with blood vessel segmentation in retinal image data. The theoretical part is focused on the basic description of anatomy and physiology of the eye and methods of observing the back of the eye. This thesis also describes the principles of classical and convolutional neural networks and segmentation techniques that are used to segment blood vessel in retinal images. In the practical part, a segmentation method using convolutional neural network U-net is implemented. This neural network is trained on the three datasets. Two datasets include images from experimental video ophthalmoscope. Because it impossible to compare the results of these two datasets with any other methods of retinal blood vessel segmentation, U-net is trained on other dataset that is HRF database. This dataset includes fundus images. The results of testing on this dataset serves for comparing results with other methods of retinal blood vessel segmentation.
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Blood vessel segmentation in retinal image data
Vančurová, Johana ; Mézl, Martin (referee) ; Odstrčilík, Jan (advisor)
This master´s thesis deals with blood vessel segmentation in retinal image data. The theoretical part is focused on the basic description of anatomy and physiology of the eye and methods of observing the back of the eye. This thesis also describes the principles of classical and convolutional neural networks and segmentation techniques that are used to segment blood vessel in retinal images. In the practical part, a segmentation method using convolutional neural network U-net is implemented. This neural network is trained on the three datasets. Two datasets include images from experimental video ophthalmoscope. Because it impossible to compare the results of these two datasets with any other methods of retinal blood vessel segmentation, U-net is trained on other dataset that is HRF database. This dataset includes fundus images. The results of testing on this dataset serves for comparing results with other methods of retinal blood vessel segmentation.
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Sensing eye movement using a device BIOPAC and eyetracker Pupil
Vančurová, Johana ; Mézl, Martin (referee) ; Svozilová, Veronika (advisor)
This bachelor thesis is focused on investigation of visual reaction time of driver using eye movements acquivition. Eye movements were acquired by Biopac device and eyetracker Pupil. The main aim of this work is to compare results of own experiments with points of reference. Theoretical part dealt with anatomy, physiology of eye and describing characteristics of EOG signals. Practical part included experimental measurements to which a group of probands was involved. In the last part of this work the obtained results were compared with the points of reference.
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