Abstract
Active contours, or Snakes, have been widely used in image processing and computer vision and intensively studied over the last two decades. The philosophy of these models involves designing the internal and external forces and the external force drives the contours to locate objects in images. This paper presents a novel external force called gradient vector convolution (GVC) for active contours. The proposed method is motivated by gradient vector flow (GVF) and possesses some advantages of GVF, such as enlarged capture range, initialization insensitivity and high performance on concavity convergence; in addition, it can be implemented in real time owing to its convolution mechanism. Some experiments are presented to demonstrate the effectiveness of the proposed method.
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Wang, Y., Jia, Y. (2008). External Force for Active Contours: Gradient Vector Convolution. In: Ho, TB., Zhou, ZH. (eds) PRICAI 2008: Trends in Artificial Intelligence. PRICAI 2008. Lecture Notes in Computer Science(), vol 5351. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89197-0_43
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DOI: https://doi.org/10.1007/978-3-540-89197-0_43
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