Obiekt
Tytuł: Surrogate data: a novel approach to object detection
Współtwórca:
Korbicz, Józef (1951- ) - red. ; Uciński, Dariusz - red.
Tytuł publikacji grupowej:
Abstract:
In the present study a novel method is introduced to detect meaningful regions of a gray-level noisy images of binary structures. The method consists in generating surrogate data for an analyzed image. A surrogate image has the same (or almost the same) power spectrum and histogram of gray-level values as the original one but is random otherwise. ; Then minmax paths are generated in the original image, each characterized by its length, minmax intensity and the intensity of the starting point. If the probability of the existence of a path with the same characteristics but within surrogate images is lower than some user-specified threshold, it is concluded that the path in the original image passes through a meaningful object. The performance of the method is tested on images corrupted by noise with varying intensity.
Wydawca:
Zielona Góra: Uniwersytet Zielonogórski
Identyfikator zasobu:
DOI:
Strony:
Źródło:
AMCS, Volume 20, Number 3 (2010) ; kliknij tutaj, żeby przejść
Jezyk:
Prawa do dysponowania publikacją:
Biblioteka Uniwersytetu Zielonogórskiego
Kolekcje, do których przypisany jest obiekt:
- Repozytorium > Jednostki organizacyjne > Wydział Informatyki, Elektrotechniki i Automatyki
- Repozytorium > Typy utworów > Artykuły
- Repozytorium > Czasopisma naukowe i serie wydawnicze UZ > International Journal of Applied Mathematics and Computer Science (AMCS)
- Repozytorium > Czasopisma naukowe i serie wydawnicze UZ > International Journal of Applied Mathematics and Computer Science (AMCS) > International Journal of Applied Mathematics and Computer Science (AMCS) (2010)
Data ostatniej modyfikacji:
2024-11-05
Data dodania obiektu:
2018-08-14
Liczba wyświetleń treści obiektu:
161
Wszystkie dostępne wersje tego obiektu:
https://zbc.uz.zgora.pl/repozytorium/publication/54967
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| Nazwa wydania | Data |
|---|---|
| Surrogate data: a novel approach to object detection | 2024-11-05 |
