TITLE:
Centerline Extraction for Image Segmentation Using Gradient and Direction Vector Flow Active Contours
AUTHORS:
Shuqun Zhang, Jianyang Zhou
KEYWORDS:
Image Segmentation; Active Contours; Gradient Vector Flow; Direction Vector Flow
JOURNAL NAME:
Journal of Signal and Information Processing,
Vol.4 No.4,
November
6,
2013
ABSTRACT: In this paper, we propose a fast centerline extraction method to be used for gradient and direction vector flow of active contours. The gradient and direction vector flow is a recently reported active contour model capable of significantly improving the image segmentation performance especially for complex object shape, by seamlessly integrating gradient vector flow and prior directional information. Since the prior directional information is provided by manual line drawing, it can be inconvenient for inexperienced users who might have difficulty in finding the best place to draw the directional lines to achieve the best segmentation performance. This paper describes a method to overcome this problem by automatically extracting centerlines to guide the users for providing the right directional information. Experimental results on synthetic and real images demonstrate the feasibility of the proposed method.