Region growing based on extended gradient vector flow field model for multiple objects segmentation
Cheng-Hung Chuang, Wen‐Nung Lie · 2002
For image segmentation, traditional snake algorithms are often short of the requirement of human interaction and capability in processing multiple objects simultaneously. Watershed techniques however have the drawback of over-segmentation. A new region growing algorithm based on the extended gradient vector flow (E-GVF) field model is proposed for multiple object segmentation. The proposed force field propagates gradient information of object boundaries and provides a good feature for region growing. We perform scoring and selection of seeds by considering their local gradient direction information. This step is automatic and requires no human interaction, making our algorithm suitable for applications. Experiments show that our algorithm is noise-resistant and also resolves the abovementioned drawbacks for snakes and watershed methods. We have tested our algorithm in segmenting multiple objects from realistic and even medical CT images and gained good results.