| Abstract [eng] |
Computer stereo vision is a receiving of stereo information from digital images. This field of science is rather new and its popularity is increasing rapidly. Computer stereo vision is applied in robotics, manufacturing industry, everyday life and other spheres. The aim of the Thesis is to analyze and compare the stereo vision algorithms. In order to achieve the aim of the Research, the following tasks are determined: to classify the stereo vision algorithms, to study the methods of algorithm design, to create the method of assessment of stereo vision algorithms and to assess the stereo vision algorithms basing on the ground of this method. Basing on academic works of various authors, the stereo vision algorithms are classified and divided into two groups in accordance with the modes of their functioning: local and global algorithms. Several algorithms are chosen from each group. A based local algorithm with different mathematical solutions is chosen from the group of local algorithms, and the dynamic programming is chosen from the group of the global algorithms. The chosen algorithms are tested in the course of the Research. To compare the mentioned algorithms, the assessment method is prepared, the main criteria of which are the correlation index and the running time of algorithm. All abovementioned algorithms are tested by the means of the method of assessment. The best results are chosen basing on the method and results of the tests. The results of the conducted Research show that the tested algorithms are not perfect, but they are appropriate for use with some limitations. Moreover, the imperfection of algorithms evidences that the abovementioned field of science has not been studied completely what affords to the scientists the ground for further development of existing algorithms and creation of the new ones. |
