Active Contour External Force Using Vector Field Convolution for Image Segmentation

• Published in: IEEE transactions on image processing Vol. 16; no. 8; pp. 2096 - 2106
• Main Authors: Bing Li, Acton, S.T.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.08.2007; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Active contours; Algorithms; Applied sciences; Computer Simulation; Convergence; Convolution; deformable models; Detection, estimation, filtering, equalization, prediction; Exact sciences and technology; external force; gradient vector flow (GVF); Image Enhancement - methods; Image generation; Image Interpretation, Computer-Assisted - methods; Image processing; Image segmentation; Imaging, Three-Dimensional - methods; Information, signal and communications theory; Kernel; Kernels; Mathematical analysis; Mathematical models; Miscellaneous; Models, Theoretical; Noise reduction; Parameter estimation; Pattern recognition; Reproducibility of Results; Sensitivity and Specificity; Shape; Signal and communications theory; Signal processing; Signal, noise; snakes; Stress, Mechanical; Studies; Technological innovation; Telecommunications and information theory; vector field convolution (VFC); Vectors (mathematics); Performance evaluation; Cost minimization; Parameter estimation; Image processing; Noise reduction; snakes; deformable models; Shape detection; Flexibility; Active contours; gradient vector flow (GVF); Innovation; Convolution; Imaging; Vector field; Active contour; Cost lowering; Deformable model; Computational complexity; Kernel method; vector field convolution (VFC); Image segmentation; external force; Analytical method; Signal processing; Noise immunity; Edge detection
• ISSN: 1057-7149; 1941-0042
• DOI: 10.1109/TIP.2007.899601

Snakes, or active contours, have been widely used in image processing applications. Typical roadblocks to consistent performance include limited capture range, noise sensitivity, and poor convergence to concavities. This paper proposes a new external force for active contours, called vector field convolution (VFC), to address these problems. VFC is calculated by convolving the edge map generated from the image with the user-defined vector field kernel. We propose two structures for the magnitude function of the vector field kernel, and we provide an analytical method to estimate the parameter of the magnitude function. Mixed VFC is introduced to alleviate the possible leakage problem caused by choosing inappropriate parameters. We also demonstrate that the standard external force and the gradient vector flow (GVF) external force are special cases of VFC in certain scenarios. Examples and comparisons with GVF are presented in this paper to show the advantages of this innovation, including superior noise robustness, reduced computational cost, and the flexibility of tailoring the force field.