Abstract
Snakes, or active contours, are used extensively in computer vision and image processing applications, particularly in locating object boundaries. Problems associated with initialization and poor convergence to boundary concavities have limited their utility. Gradient vector flow (GVF) snake solved both problems successfully. However, boundaries in noisy images are often blurred even destroyed with smoothing and false results usually occur when such images are processed even with GVF snake model. We have incorporated embedded edge confidence (EEC) into GVF snake model. The improved method can solve this problem when noisy images were processed.
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© 2004 Springer-Verlag Berlin Heidelberg
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Wang, Y., Yang, J. (2004). Gradient Vector Flow Snake with Embedded Edge Confidence. In: Zhang, C., W. Guesgen, H., Yeap, WK. (eds) PRICAI 2004: Trends in Artificial Intelligence. PRICAI 2004. Lecture Notes in Computer Science(), vol 3157. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28633-2_82
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DOI: https://doi.org/10.1007/978-3-540-28633-2_82
Publisher Name: Springer, Berlin, Heidelberg
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