Shape-Based Image Segmentation Using Normalized Cuts

To segment a whole object from an image is an essential and challenging task in image processing. In this paper, we propose a hybrid segmentation algorithm which combines prior shape information with normalized cut. With the help of shape information, we can utilize normalized cut to correctly segment the target whose boundary may be corrupted by noise or outliers. At the same time, we introduce the use of segmentation results of the normalized cut to guide the shape model, and thus avoid searching the shape space. The proposed method was demonstrated to be effective by our experiments on both synthetic and real data.

• Type: Conference
• Year: 2006
• Where: ICIP
• Authors: Wenchao Cai, Jue Wu, Albert C. S. Chung
• Keywords: Hybrid Segmentation Algorithm, ICIP 2006, Image Processing, Normalized Cut, Shape Information, Shape Space