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National Repository of Grey Literature 12 records found  previous11 - 12  jump to record: Search took 0.00 seconds. 
Long-term Analysis of Ultrasound Video Sequences Using Interest Point Detectors
 Zukal, Martin ; Závodná, Eva (referee) ; Papež,, Václav (referee) ; Říha, Kamil (advisor)
This doctoral thesis deals with the analysis of ultrasound (US) video sequences. It specifically focuses on long-term tracking of the common carotid artery (CCA) in transversal section and measurement of its geometric parameters in a sequence of US images. The design and implementation of a system for automatic tracking of the artery is described in this thesis. The proposed system utilizes Viola-Jones detector and Hough transform to localize the artery in the image. Interest points are detected in the area of the artery wall. These points are then tracked using optical flow. The proposed system comprises a number of innovative methods which allow to perform accurate long-term measurement of parameters of CCA and store the results. A novel mathematical model describing the movement of CCA in transversal section during a cardiac cycle is defined afterwards taking the influence of breathing into consideration. A number of artificial sequences of US images based on this model have been created. These sequences were consequently used to evaluate the accuracy of the proposed system in terms of measuring the parameters of CCA. The sequences are unique because of their length which makes them suitable for evaluation of tracking accuracy even in long video sequences.
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Image similarity measurement using points of interest
 Jelínek, Ondřej ; Uher, Václav (referee) ; Burget, Radim (advisor)
This paper presents a new object detection method. The method is based on keypoints analysis and their parameters. Computed parameters are used for building a decision model using machine learning methods. The model is able to detect object in the picture based on input data and compares its similarity to the chosen example. The new method is described in detail, its accuracy is evaluated and this accuracy is compared to other existing detectors. The new method’s detection ability is by more than 40% better than detection ability of detectors like SURF. In order to understand the object detection this paper describes the process step by step including popular algorithms designed for specific roles in each step.
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National Repository of Grey Literature : 12 records found   previous11 - 12  jump to record:
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