Title :
Symmetry integrated region-based image segmentation
Author :
Yu Sun ; Bhanu, Bir
Author_Institution :
Center for Res. in Intell. Syst., Univ. of California at Riverside, Riverside, CA, USA
Abstract :
Symmetry is an important cue for machine perception that involves high-level knowledge of image components. Unlike most of the previous research that only computes symmetry in an image, this paper integrates symmetry with image segmentation to improve the segmentation performance. The symmetry integration is used to optimize both the segmentation and the symmetry of regions simultaneously. Interesting points are initially extracted from an image and they are further refined for detecting symmetry axis. A symmetry affinity matrix is used explicitly as a constraint in a region growing algorithm in order to refine the symmetry of segmented regions. Experimental results and comparisons from a wide domain of images indicate a promising improvement by symmetry integrated image segmentation compared to other image segmentation methods that do not exploit symmetry.
Keywords :
image segmentation; matrix algebra; object detection; image component; image segmentation; machine perception; region growing algorithm; symmetry affinity matrix; symmetry axis detection; symmetry integrated region; Computer vision; Image edge detection; Image segmentation; Intelligent systems; Machine intelligence; Noise shaping; Object detection; Robustness; Shape; Sun;
Conference_Titel :
Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on
Conference_Location :
Miami, FL
Print_ISBN :
978-1-4244-3992-8
DOI :
10.1109/CVPR.2009.5206570