Title :
A segmentation approach for object detection on highly dynamic aquatic environments
Author :
Nuno, Peixoto P. ; Nuno, Cardoso G. ; Jorge, Cabral M. ; Adriano, Tavares J. ; José, Mendes A.
Author_Institution :
Univ. of Minho, Minho, Portugal
Abstract :
The majority of segmentation methods applied to outdoor environments are not suitable to highly dynamic backgrounds, like in an outdoor swimming pool. This paper presents a new method for image segmentation of objects with a background with random noise generated by water oscillation. The key feature of this segmentation method is based on processing hue component of color in HSV color space on a predetermined image area. This component is not affected by reflections, splashes, random water movements and overall scene light changes on the water surface. Foreground is extracted based on combination of temporal background estimation with spatial correction and inter-frame subtraction. The algorithm was applied and tested in a real situation, specifically on an outdoor domestic pool, showing good robustness and reliability with less computational load.
Keywords :
image colour analysis; image segmentation; object detection; random noise; HSV color space; highly dynamic aquatic environment; image segmentation; interframe subtraction; object detection; outdoor domestic pool; random noise; spatial correction; temporal background estimation; water oscillation; Acoustic reflection; Background noise; Color; Colored noise; Image segmentation; Layout; Noise generators; Object detection; Optical reflection; Working environment noise;
Conference_Titel :
Industrial Electronics, 2009. IECON '09. 35th Annual Conference of IEEE
Conference_Location :
Porto
Print_ISBN :
978-1-4244-4648-3
Electronic_ISBN :
1553-572X
DOI :
10.1109/IECON.2009.5414893