Accelerating active contour algorithms with the Gradient Diffusion Field

Active contours were proposed by Kass et al. as a way to represent the contours of an image. Although the method is simple, one of its shortcomings is its inability to converge into concave structures. The gradient vector flow (GVF) algorithm was put forth by Xu and Prince to succesfully address the concave structure problem. Although there has been much research into GVF, little has been done to reduce its computation time, which makes it unsuitable for applications requiring real-time processing of images. In this paper, we propose a method for computing an approximation of the GVF, called the gradient diffusion field (GDF), which exhibits the same useful properties of the GVF but converges faster and requires less resources for implementation. Our proposed method is also more amenable for real-time hardware and we outline a method for implementing an active contour algorithm in FPGA hardware using the GDF.

[1]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  Chih-Yang Lin,et al.  Rectangular meshes construction of the human urethra using 3D GVF snakes , 2004, SPIE Medical Imaging.

[3]  Jerry L. Prince,et al.  Snakes, shapes, and gradient vector flow , 1998, IEEE Trans. Image Process..

[4]  Aggelos K. Katsaggelos,et al.  Lip tracking for MPEG-4 facial animation , 2002, Proceedings. Fourth IEEE International Conference on Multimodal Interfaces.

[5]  Nikos Paragios,et al.  Gradient vector flow fast geometric active contours , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[6]  Demetri Terzopoulos,et al.  Snakes: Active contour models , 2004, International Journal of Computer Vision.

[7]  Mubarak Shah,et al.  A Fast algorithm for active contours and curvature estimation , 1992, CVGIP Image Underst..

[8]  Terry E. Weymouth,et al.  Using Dynamic Programming For Minimizing The Energy Of Active Contours In The Presence Of Hard Constraints , 1988, [1988 Proceedings] Second International Conference on Computer Vision.

[9]  Nikos Paragios,et al.  Gradient Vector Flow Fast Geodesic Active Contours , 2001, ICCV.