Temat: rozpoznawanie dłoni - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Contactless person identification based on double-sided 3D scan of hand geometry
Autorzy:: Nowak, Piotr Stefan
Sankowski, Wojciech
Krotewicz, Paweł
Zubert, Mariusz
Powiązania:: https://bibliotekanauki.pl/articles/397789.pdf
Data publikacji:: 2018
Wydawca:: Politechnika Łódzka. Wydział Mikroelektroniki i Informatyki
Tematy:: biometrics
contactless identification
hand recognition
biometria
identyfikacja zbliżeniowa
rozpoznawanie dłoni
Opis:: This paper presents person identification algorithm based on 3D hand geometry. The algorithm comprises the following phases of 3D hand scan processing: segmentation, feature extraction and comparison, which the authors explain in detail in the paper. The authors present results of algorithm performance tested on publicly available DMCSv1 database which contains 1400 samples of 3D hand scans of left and right hand acquired from 35 individuals. Obtained values of equal error rate are 16% for the left hand scans, 17% for the right hand scan sand the values of rank-1 accuracy are 85% and 82% for the left and right hand scans, respectively.
Źródło:: International Journal of Microelectronics and Computer Science; 2018, 9, 3; 85-92
2080-8755
2353-9607
Pojawia się w:: International Journal of Microelectronics and Computer Science
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Applying hand gesture recognition with time-of-flight camera for 3D medical data analysis
Autorzy:: Malawski, F.
Powiązania:: https://bibliotekanauki.pl/articles/115723.pdf
Data publikacji:: 2014
Wydawca:: Fundacja na Rzecz Młodych Naukowców
Tematy:: human-computer interaction
hand gesture recognition
time-of-flight camera
interakcja człowiek-komputer
rozpoznawanie gestów dłoni
czas przelotu kamery
Opis:: This paper describes a human-computer interface based on hand gesture recognition, intended for analysis of 3D medical data. The gestures are designed to minimize the required muscle tension when using the system. Gesture recognition is based on a 3D sensor. Depth maps are acquired by a time-of-flight camera, designed specifically for hand gestures recognition. The depth images are denoised and segmented to right and left hand. The contours of the hands are found and a modified Shape Context descriptor is utilized for each hand, providing a set of features, which are employed to train and test various classifiers. Naive Bayes, Random Forest and Support Vector Machine (SVM) classifiers are utilized, with search of optimal parameters using cross-validation. The best accuracy (95%) is achieved with the Support Vector Machine classifier. The gestures are mapped to various controls of a 3D medical visualization module. Two visualization methods are employed - isosurface and cut-planes. The left hand is assigned to switching between different control modes and the right hand gestures are corresponding to controlling various properties in each mode. The system is convenient to use and runs in real-time on a typical PC machine.
Źródło:: Challenges of Modern Technology; 2014, 5, 4; 12-16
2082-2863
2353-4419
Pojawia się w:: Challenges of Modern Technology
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Picture Languages in Automatic Radiological Palm Interpretation
Autorzy:: Tadeusiewicz, R.
Ogiela, M. R.
Powiązania:: https://bibliotekanauki.pl/articles/908539.pdf
Data publikacji:: 2005
Wydawca:: Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:: komputerowe wspomaganie diagnozy
diagnostyka choroby
choroba dłoni
syntaktyczne rozpoznawanie obrazu
rozumienie obrazu
medyczna analiza obrazu
syntactic pattern recognition
image understanding
medical image analysis
computer-aided diagnosis
palm disease diagnostics
Opis:: The paper presents a new technique for cognitive analysis and recognition of pathological wrist bone lesions. This method uses AI techniques and mathematical linguistics allowing us to automatically evaluate the structure of the said bones, based on palm radiological images. Possibilities of computer interpretation of selected images, based on the methodology of automatic medical image understanding, as introduced by the authors, were created owing to the introduction of an original relational description of individual palm bones. This description was built with the use of graph linguistic formalisms already applied in artificial intelligence. The research described in this paper demonstrates that for the needs of palm bone diagnostics, specialist linguistic tools such as expansive graph grammars and EDT-label graphs are particularly well suited. Defining a graph image language adjusted to the specific features of the scientific problem described here permitted a semantic description of correct palm bone structures. It also enabled the interpretation of images showing some in-born lesions, such as additional bones or acquired lesions such as their incorrect junctions resulting from injuries and synostoses.
Źródło:: International Journal of Applied Mathematics and Computer Science; 2005, 15, 2; 305-312
1641-876X
2083-8492
Pojawia się w:: International Journal of Applied Mathematics and Computer Science
Dostawca treści:: Biblioteka Nauki

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