TY - GEN
T1 - A new information fusion approach for image segmentation
AU - Xu, Wentao
AU - Kanawong, Ratchadaporn
AU - Duan, Ye
AU - Zhang, Guixu
PY - 2011
Y1 - 2011
N2 - In this paper we propose a new hybrid image segmentation algorithm that integrate the region-based method with the boundary-based method. More specifically we take an information fusion approach based on the Tensor Voting framework that seamlessly fuse the information from the region-based Mean Shift method with the boundary-based Canny Edge Detection algorithm. We have tested our algorithm on several images from the Caltech 101 database [18]. Experiments results show the new algorithm is very efficient and can achieve very good segmentation results.
AB - In this paper we propose a new hybrid image segmentation algorithm that integrate the region-based method with the boundary-based method. More specifically we take an information fusion approach based on the Tensor Voting framework that seamlessly fuse the information from the region-based Mean Shift method with the boundary-based Canny Edge Detection algorithm. We have tested our algorithm on several images from the Caltech 101 database [18]. Experiments results show the new algorithm is very efficient and can achieve very good segmentation results.
KW - Hybrid image segmentation
KW - Information fusion
UR - https://www.scopus.com/pages/publications/84863030275
U2 - 10.1109/ICIP.2011.6116148
DO - 10.1109/ICIP.2011.6116148
M3 - 会议稿件
AN - SCOPUS:84863030275
SN - 9781457713033
T3 - Proceedings - International Conference on Image Processing, ICIP
SP - 2873
EP - 2876
BT - ICIP 2011
T2 - 2011 18th IEEE International Conference on Image Processing, ICIP 2011
Y2 - 11 September 2011 through 14 September 2011
ER -