Temat: Features - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Method of signature recognition with the use of the complex features
Autorzy:: Doroz, R.
Pałys, M.
Orczyk, T.
Safaverdi, H.
Powiązania:: https://bibliotekanauki.pl/articles/333247.pdf
Data publikacji:: 2014
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: biometrics
signature recognition
complex features
biometria
rozpoznawanie podpisu
funkcje złożone
Opis:: In this paper a new method of handwritten signatures verification has been proposed. This method, for each signature, creates complex features which are describing this signature. These features are based on dependencies analysis between dynamic features registered by tablets. These complex features are then used to create vectors describing the signature. Elements of these vectors are calculated using measures proposed in this work. The similarity between signatures is assessed by determining the similarity of vectors in the compared signatures. Research, whose results will be presented in the further part of this work, have shown a high efficiency of verification using proposed method.
Źródło:: Journal of Medical Informatics & Technologies; 2014, 23; 155-162
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 2.

Tytuł:: Personal identity verification method based on lips photographs
Autorzy:: Wrobel, K.
Doroz, R.
Porwik, P.
Naruniec, J.
Kowalski, M.
Powiązania:: https://bibliotekanauki.pl/articles/333548.pdf
Data publikacji:: 2015
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: biometrics
lip features
data classification
biometria
cechy wargi
klasyfikacja danych
Opis:: The paper presents a personal identification method based on lips photographs. This method uses a new approach to the extraction and classification of characteristic features of the mouth from photographs. It eliminates the drawbacks that occur during the acquisition of lip print images with the use of the forensic method that requires special tools. Geometrical dimensions of the entire mouth as well as of the upper and lower lips were adopted as the features, on the basis of which the verification is performed. An ensemble classifier was used for the classification of the features obtained. The effectiveness of the classifier has been verified experimentally.
Źródło:: Journal of Medical Informatics & Technologies; 2015, 24; 59-65
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 3.

Tytuł:: Signatures recognition method by using the normalized Levenshtein distances
Autorzy:: Doroz, R.
Wróbel, K.
Porwik, P.
Powiązania:: https://bibliotekanauki.pl/articles/333029.pdf
Data publikacji:: 2009
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: rozpoznawanie podpisu
właściwości dynamiczne
odległość Levenshteina
signature recognition
dynamic features
Levenshtein distance
Opis:: This study examines the effectiveness of normalized Levenshtein metrics in the process of recognition of handwritten signatures. Three methods of normalization of the Levenshtein metric were taken into consideration. In addition, it was determined, which signature features are most important during their comparisons with the use of the aforementioned metric. The following signature features were examined: coordinates of signature points, pen pressure in successive points, and different types of pen speed. The influence of individual parameters of the Levenshtein algorithm on the obtained results was also determined, and the best method of normalization was selected.
Źródło:: Journal of Medical Informatics & Technologies; 2009, 13; 73-77
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 4.

Tytuł:: New methods to determine similarity of signatures based on local extremes
Autorzy:: Doroz, R.
Mitas, M.
Powiązania:: https://bibliotekanauki.pl/articles/332892.pdf
Data publikacji:: 2008
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: podpis własnoręczny
dynamiczne cechy podpisu
metody regresji liniowej
dynamiczny czas wypaczania
handwritten signatures
dynamic signature features
linear regression method
dynamic time warping
Opis:: Authentication based on handwritten signature is one of the most accepted authentication systems based on biometry. In this paper a method for the automatic verification of on-line handwritten signatures using three similarity measures is described. The proposed approach, is based on extreme values and dynamic features of the signature. In investigations proposed coefficients together with the factor [R2] were connected and new signature recognition quality has been achieved.
Źródło:: Journal of Medical Informatics & Technologies; 2008, 12; 63-67
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

Artykuł

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