Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

Wyszukujesz frazę "feature matching" wg kryterium: Temat


Wyświetlanie 1-2 z 2
Tytuł:
Depth-based Descriptor for Matching Keypoints in 3D Scenes
Autorzy:
Matusiak, K.
Skulimowski, P.
Strumillo, P.
Powiązania:
https://bibliotekanauki.pl/articles/226051.pdf
Data publikacji:
2018
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
feature matching
keypoints detection
object recognition
depth map
Opis:
Keypoint detection is a basic step in many computer vision algorithms aimed at recognition of objects, automatic navigation and analysis of biomedical images. Successful implementation of higher level image analysis tasks, however, is conditioned by reliable detection of characteristic image local regions termed keypoints. A large number of keypoint detection algorithms has been proposed and verified. In this paper we discuss the most important keypoint detection algorithms. The main part of this work is devoted to description of a keypoint detection algorithm we propose that incorporates depth information computed from stereovision cameras or other depth sensing devices. It is shown that filtering out keypoints that are context dependent, e.g. located at boundaries of objects can improve the matching performance of the keypoints which is the basis for object recognition tasks. This improvement is shown quantitatively by comparing the proposed algorithm to the widely accepted SIFT keypoint detector algorithm. Our study is motivated by a development of a system aimed at aiding the visually impaired in space perception and object identification.
Źródło:
International Journal of Electronics and Telecommunications; 2018, 64, 3; 299-306
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Determination of the Optimal Threshold Value and Number of Keypoints in Scale Invariant Feature Transform-based Copy-Move Forgery Detection
Autorzy:
Isnanto, R. Rizal
Zahra, Ajub Ajulian
Santoso, Imam
Lubis, Muhammad Salman
Powiązania:
https://bibliotekanauki.pl/articles/227299.pdf
Data publikacji:
2020
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
forgery
Gaussian noise
feature extraction
pattern matching
Euclidean distance
Opis:
The copy-move forgery detection (CMFD) begins with the preprocessing until the image is ready to process. Then, the image features are extracted using a feature-transform-based extraction called the scale-invariant feature transform (SIFT). The last step is features matching using Generalized 2 Nearest-Neighbor (G2NN) method with threshold values variation. The problem is what is the optimal threshold value and number of keypoints so that copy-move detection has the highest accuracy. The optimal threshold value and number of keypoints had determined so that the detection n has the highest accuracy. The research was carried out on images without noise and with Gaussian noise.
Źródło:
International Journal of Electronics and Telecommunications; 2020, 66, 3; 561-569
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

    Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies