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Delineation of ECG signals using phasor transform
Koupil, Michal ; Vítek, Martin (referee) ; Maršánová, Lucie (advisor)
TThis project deals with delineation of ECG signals using phasor transform. This method is rather new in the field of automatic delineation of ECG and it is not widely used in practice yet. In the theoretical part, the relation between heart activity and ECG is described. A phasor transform is also described. In the practical part, a program was implemented in the computing environment of MATLAB. Its purpose is to delineate the signals. At first, it detects waves’ peaks, then its beginning and starting points. In the next part, analysis of the results is done, as well as comparison with other authors. The testing was performed on the QT signals from the Physionet database.
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Biometrics using Face Recognition
Koupil, Michal ; Mézl, Martin (referee) ; Odstrčilík, Jan (advisor)
This work is focused on a face detection in a picture and subsequent recognition of the face in its respective database. Face detection had been implemented using Viola-Jones algorithm. To recognize the face afterwards, PCA (Principal Component Analysis) a LBPH (Local Binary Pattern Histograms) had been used. Implemented algorithm had been tested on freely accesible biometric databases. Overall success rate of face detection was 93,4 %. Overall success rate of face recognition using PCA was 88,1 % and with LBPH it was 93,1 %. Of the two methods for face recognition, LBPH method has better ability to perform recognition with data, that do not possess ideal parameters for biometrics. With data suitable for biometrics, both of the methods perform well, with PCA being faster.
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Biometrics using Face Recognition
Koupil, Michal ; Mézl, Martin (referee) ; Odstrčilík, Jan (advisor)
This work is focused on a face detection in a picture and subsequent recognition of the face in its respective database. Face detection had been implemented using Viola-Jones algorithm. To recognize the face afterwards, PCA (Principal Component Analysis) a LBPH (Local Binary Pattern Histograms) had been used. Implemented algorithm had been tested on freely accesible biometric databases. Overall success rate of face detection was 93,4 %. Overall success rate of face recognition using PCA was 88,1 % and with LBPH it was 93,1 %. Of the two methods for face recognition, LBPH method has better ability to perform recognition with data, that do not possess ideal parameters for biometrics. With data suitable for biometrics, both of the methods perform well, with PCA being faster.
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Delineation of ECG signals using phasor transform
Koupil, Michal ; Vítek, Martin (referee) ; Maršánová, Lucie (advisor)
TThis project deals with delineation of ECG signals using phasor transform. This method is rather new in the field of automatic delineation of ECG and it is not widely used in practice yet. In the theoretical part, the relation between heart activity and ECG is described. A phasor transform is also described. In the practical part, a program was implemented in the computing environment of MATLAB. Its purpose is to delineate the signals. At first, it detects waves’ peaks, then its beginning and starting points. In the next part, analysis of the results is done, as well as comparison with other authors. The testing was performed on the QT signals from the Physionet database.
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