This paper presents an active method for locating objects in images, which is conceptualized mainly by elastically deformable contour model. When an initial model is applied to an image data, it attracts near dominant image features such as edges or lines, but tries to keep its home shape or smooth the deformation if a deformation from the home shape occurs. This model is characterized by the core and the rigidity coefficients which control the shape and strength with the prior knowledge about the expected shape of the object. This mechanism significantly improves the performance of detecting object boundaries in presence of some disturbing image features. The proposed method is validated through a series of experiments, which include tracking objects under nonrigid motion and comparison with the original snake models.
展开▼
