|
|
Image objects detection based on the feature points matching
Trávníček, Vojtěch ; Macíček, Ondřej (referee) ; Harabiš, Vratislav (advisor)
This paper is concerned in branch of computer vision. Methods for extracting feature points are presented as tools for image comparison and finding objects in images. Four methods are metioned which are compared with respect to their effectiveness and utilization. Algorythms SIFT and SURF are described as a state-of-the-arts. This paper also mentions methods for describing feature points and their comparison. Testing images are inserted as a tool for first testing of implemented algorythm. Finally, the implemented method SURF is described and tested with respect to several most relevant parameters.
|
|
|
Robust Screen and Slide Detection in Video
Hanzel, Svätopluk ; Beran, Vítězslav (referee) ; Szőke, Igor (advisor)
The main goal of this bachelor thesis is implementation of a robust screen detector with slide synchronization using various techniques including neural networks, keypoints extraction and matching, text extraction using OCR and text matching. These methods are also analysed and compared to their possible alternatives.
|
|
|
Robust Screen and Slide Detection in Video
Hanzel, Svätopluk ; Beran, Vítězslav (referee) ; Szőke, Igor (advisor)
The main goal of this bachelor thesis is implementation of a robust screen detector with slide synchronization using various techniques including neural networks, keypoints extraction and matching, text extraction using OCR and text matching. These methods are also analysed and compared to their possible alternatives.
|
|
|
Image objects detection based on the feature points matching
Trávníček, Vojtěch ; Macíček, Ondřej (referee) ; Harabiš, Vratislav (advisor)
This paper is concerned in branch of computer vision. Methods for extracting feature points are presented as tools for image comparison and finding objects in images. Four methods are metioned which are compared with respect to their effectiveness and utilization. Algorythms SIFT and SURF are described as a state-of-the-arts. This paper also mentions methods for describing feature points and their comparison. Testing images are inserted as a tool for first testing of implemented algorythm. Finally, the implemented method SURF is described and tested with respect to several most relevant parameters.
|
guest ::
