Finding a Closed Boundary by Growing Minimal Paths from a Single Point
Bonneau, Stéphane; Benmansour, Fethallah; Cohen, Laurent D. (2007), Finding a Closed Boundary by Growing Minimal Paths from a Single Point, in Jorge, R. M. Natal; Tavares, João Manuel R. S., Computational vision and medical image processing, proceedings of VipIMAGE 2007, Taylor & Francis Ltd : London
TypeCommunication / Conférence
Conference titleVIPIMAGE 2007
Book titleComputational vision and medical image processing, proceedings of VipIMAGE 2007
Book authorJorge, R. M. Natal; Tavares, João Manuel R. S.
Number of pages396
MetadataShow full item record
Abstract (EN)In this paper, we present a new method for segmenting closed contours. Our work builds on a variant of the Fast Marching algorithm. First, an initial point on the desired contour is chosen by the user. Next, new keypoints are detected automatically using a front propagation approach. We assume that the desired object has a closed boundary. This a-priori knowledge on the topology is used to devise a relevant criterion for stopping the keypoint detection and front propagation. The final domain visited by the front will yield a band surrounding the object of interest. Linking pairs of neighboring keypoints with minimal paths allows us to extract a closed contour from a 2D image. Detection of a variety of objects on real images is demonstrated.
Subjects / KeywordsComputer vision in medicine; image segmentation
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