Publication detail
Circle Detection in Pulsative Medical Video Sequence
ŘÍHA, K. BENEŠ, R.
Original Title
Circle Detection in Pulsative Medical Video Sequence
Czech Title
Detekce kružnic v sekvenci obsahující pulsující pohyb
English Title
Circle Detection in Pulsative Medical Video Sequence
Type
conference paper
Language
en
Original Abstract
The article deals with a new method for the detection of pulsative circular objects in a medical video sequence. The motivation for investigating this method consists in the fact that a circular object is not very apparent and its detection in such a frame is inaccurate. In some cases of medical images, the pulsative character of the circular area being searched can be used for its localisation. The proposed method starts from an analysis of movement, using optical flow estimation. The compensation of global movement is necessary because only local pulsative movement during the video sequence is assumed. The optical flow estimation is followed by another main processing step: the Hough Transform for the circle position estimation. Circles with expected properties are selected using the Bayes classifier. Finally, the circle position in a single frame is adapted using the analysis of average pixel intensity in the directions starting from the circle centre.
Czech abstract
Tento článek se zabývá novou metodu pro detekci kruhovitého objektu v medicínské video sekvenci, vykazujícího pulzující pohyb. Motivace výzkumu takové metody spočívá ve faktu, že v některých případech není kruhovitý objekt v jednom snímku výrazně patrný a jeho detekce v tomto snímku není úspěšná. Pokud však kruhovitá oblast vykazuje pulzující pohyb, lze využít tohoto pohybu v sekvenci snímků k její lokalizaci. Navržená metoda vychází z analýzy pohybu pomocí optického toku. Je předpokládán pouze lokální pulsující pohyb uvnitř videosekvence, proto je nutné před vlastní aplikací optického toku využít kompenzaci globálního pohybu. Po aplikaci optického toku a dalších úpravách je využito Houghovy transformace pro lokalizaci kruhu. Je také využito Bayesovského klasifikátoru pro vyhledání pouze kruhů, které vykazují očekávané vlastnosti. Nakonec je upřesněna poloha hledaného kruhu v konkrétním snímku sekvence pomocí analýzy průměrného jasu na různých oblastech.
English abstract
The article deals with a new method for the detection of pulsative circular objects in a medical video sequence. The motivation for investigating this method consists in the fact that a circular object is not very apparent and its detection in such a frame is inaccurate. In some cases of medical images, the pulsative character of the circular area being searched can be used for its localisation. The proposed method starts from an analysis of movement, using optical flow estimation. The compensation of global movement is necessary because only local pulsative movement during the video sequence is assumed. The optical flow estimation is followed by another main processing step: the Hough Transform for the circle position estimation. Circles with expected properties are selected using the Bayes classifier. Finally, the circle position in a single frame is adapted using the analysis of average pixel intensity in the directions starting from the circle centre.
Keywords
Circle detection, Video sequence, Optical flow, Hough Transform, Bayes classifyer
RIV year
2010
Released
23.10.2010
Publisher
IEEE Press
Location
Beijing
ISBN
978-1-4244-5898-1
Book
Proceedings of International Conference on Signal Processing, vol. I
Pages from
674
Pages to
677
Pages count
4
BibTex
@inproceedings{BUT33327,
author="Kamil {Říha} and Radek {Beneš}",
title="Circle Detection in Pulsative Medical Video Sequence",
annote="The article deals with a new method for the detection of pulsative circular objects in a medical video sequence. The motivation for investigating this method consists in the fact that a circular object is not very apparent and its detection in such a frame is inaccurate. In some cases of medical images, the pulsative character of the circular area being searched can be used for its localisation. The proposed method starts from an analysis of movement, using optical flow estimation. The compensation of global movement is necessary because only local pulsative movement during the video sequence is assumed. The optical flow estimation is followed by another main processing step: the Hough Transform for the circle position estimation. Circles with expected properties are selected using the Bayes classifier. Finally, the circle position in a single frame is adapted using the analysis of average pixel intensity in the directions starting from the circle centre.",
address="IEEE Press",
booktitle="Proceedings of International Conference on Signal Processing, vol. I",
chapter="33327",
howpublished="electronic, physical medium",
institution="IEEE Press",
year="2010",
month="october",
pages="674--677",
publisher="IEEE Press",
type="conference paper"
}