Title :
Mean Shift Spectral Clustering for Perceptual Image Segmentation
Author :
Ozertem, Umut ; Erdogmus, Deniz ; Lan, Tian
Author_Institution :
Dept. of Comput. Sci. Electr. Eng., Oregon Health & Sci. Univ., Portland, OR
Abstract :
Segmentation is a fundamental problem in image processing having a wide range of applications. Image segmentation algorithms in the literature range from a cost criterion based optimization techniques to various heuristic methods. In this paper, we propose utilizing mean shift spectral clustering for perceptually better image segmentation results
Keywords :
image segmentation; optimisation; heuristic methods; image processing; mean shift spectral clustering; optimization techniques; perceptual image segmentation; Clustering algorithms; Cost function; Feature extraction; Filtering; Image edge detection; Image processing; Image segmentation; Kernel; Optimization methods; Pixel;
Conference_Titel :
Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on
Conference_Location :
Toulouse
Print_ISBN :
1-4244-0469-X
DOI :
10.1109/ICASSP.2006.1660293
